bluuebunny/crossref_metadata_2025_split huggingface dataset:
TwoStabiliserloci inAntirrhinumsuppress the transposition of Tam3 without compromising transposase production
Authors: Wang Shasha , Uchiyama Takako , Kuwabara Hiroyuki , Hirata Megumi , Yuasa Ikumi , Nakahara Kenji , Martin Cathie , Kishima Yuji 
Published: June 2024

AbstractAntirrhinum majushas been known to exhibit occasional instabilities that are manifested as variegations and morphological chimeras.Stabiliser(St) is a historical locus that stabilizes phenotypically unstable or mutable traits inAntirrhinum. Here, we characterized twoStloci, the previously describedOld Stabiliser(OSt) andNew Stabiliser(NSt), inAntirrhinumthat specifically suppress the transposition of the Class II DNA transposable element, Tam3. BothStloci involve derivatives of Tam3 with unique structures:OSthas a pseudo-Tam3 copy whose 5’-terminal region has been rearranged compared to the cognate Tam3 element, andNStconsists of two intact copies of Tam3 in a head-to-head orientation. Neither locus interferes with the production of the intact Tam3 transposase (TPase) or the nuclear import of TPase.BothOStandNStproduce specific sRNAs from their 5’ terminal regions containing multiple TPase binding motifs. These specific sRNAs could repress Tam3 transposition by interacting with the TPase binding motifs within the Tam3 element or with the TPase itself.
Optimizing single-cell RNA sequencing methods for human colon biopsies: droplet-based vs. picowell-based platforms
Authors: Downie Jonathan M. , Musich Ryan J. , Geraghty Connor M. , Caraballo Alexander , He Shijie , Khawaled Saleh , Lachut Kylor , Long Timothy , Zhou Julie Y. , Yilmaz Omer H. , Stappenbeck Thaddeus , Chan Andrew T. , Drew David A. 
Published: June 2024

AbstractBackground & AimsSingle-cell RNA sequencing (scRNA) has empowered many insights into gastrointestinal microenvironments. However, profiling human biopsies using droplet-based scRNA (D-scRNA) is challenging since it requires immediate processing to minimize epithelial cell damage. In contrast, picowell-based (P-scRNA) platforms permit short-term frozen storage before sequencing. We compared P- and D-scRNA platforms on cells derived from human colon biopsies.MethodsEndoscopic rectosigmoid mucosal biopsies were obtained from two adults and conducted D-scRNA (10X Chromium) and P-scRNA (Honeycomb HIVE) in parallel using an individual’s pool of single cells (> 10,000 cells/participant). Three experiments were performed to evaluate 1) P-scRNA with cells under specific storage conditions (immediately processed [fresh], vs. frozen at -20C vs. -80C [2 weeks]); 2) fresh P-scRNA versus fresh D-scRNA; and 3) P-scRNA stored at -80C with fresh D-scRNA.ResultsSignificant recovery of loaded cells was achieved for fresh (80.9%) and -80C (48.5%) P-scRNA and D-scRNA (76.6%), but not -20C P-scRNA (3.7%). However, D-scRNA captures more typeable cells among recovered cells (71.5% vs. 15.8% Fresh and 18.4% -80C P-scRNA), and these cells exhibit higher gene coverage at the expense of higher mitochondrial read fractions across most cell types. Cells profiled using D-scRNA demonstrated more consistent gene expression profiles among the same cell type than those profiled using P-scRNA. Significant intra-cell-type differences were observed in profiled gene classes across platforms.ConclusionsOur results highlight non-overlapping advantages of P-scRNA and D-scRNA and underscore the need for innovation to enable high-fidelity capture of colonic epithelial cells. The platform-specific variation highlights the challenges of maintaining rigor and reproducibility across studies that use different platforms.
TGFβ signaling in cancer-associated fibroblasts drives a hepatic gp130-dependent pro-metastatic inflammatory program in CMS4 colorectal cancer subtype
Authors: Harryvan TJ , Abudukelimu S , Stouten I , van der Wel EJ , Janson SGT , Lenos KJ , Lannagan TRM , White M , Sansom OJ , Verdegaal EME , Hawinkels LJAC 
Published: June 2024

AbstractCurrent molecular classification of colorectal cancer (CRC), the Consensus Molecular Subtypes (CMS), has highlighted the biological heterogeneity of CRC and enables patient stratification based on the molecular subtype of their tumor. The CMS4 subtype shows the worst prognosis and is linked to the highest occurrence of hepatic metastasis but the underlying molecular mechanisms remain unclear. In this study, we show that the molecular features that largely define CMS4 classification, i.e. abundance of cancer-associated fibroblasts (CAFs) in the tumor microenvironment (TME) and active TGFβ signaling, converge to promote liver metastasis. Studying TGFβ signaling in CRC patient-derived CAFs from the primary tumor revealed that all three TGFβ isoforms induce expression of different IL-6 cytokine family members, particularly IL-6 and IL-11. This primary tumor-derived IL-6 and IL-11 in turn induce upregulation of myeloid chemoattractants, including SAA1, in hepatocytes. Chemical inhibition and genetic ablation experiments revealed that gp130, the IL-6 family of cytokine co-receptor, through JAK/STAT signaling is crucial for the induction of neutrophil chemoattractants by hepatocytes and mediates the migration of potential pro-metastatic neutrophils towards the liver. This IL-6 family-JAK/STAT stromal signaling axis is active in both a murine model of CMS4 as well as in human CRC patientsin vivo. Combined, our data reveal that TGFβ signaling in CAFs actively contributes to the formation of a neutrophil-dependent, pre-metastatic hepatic niche and that this mechanism might play a role in the metastatic phenotype of CMS4 subtype CRC.
Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma
Authors: Suita Yusuke , Bright Hardy , Pu Yuan , Toruner Merih Deniz , Idehen Jordan , Tapinos Nikos , Singh Ritambhara 
Published: June 2024

AbstractCancer cells show remarkable plasticity and can switch lineages in response to the tumor microenvironment. Cellular plasticity drives invasiveness and metastasis and helps cancer cells to evade therapy by developing resistance to radiation and cytotoxic chemotherapy. Increased understanding of cell fate determination through epigenetic reprogramming is critical to discover how cancer cells achieve transcriptomic and phenotypic plasticity.Glioblastoma is a perfect example of cancer evolution where cells retain an inherent level of plasticity through activation or maintenance of progenitor developmental programs. However, the principles governing epigenetic drivers of cellular plasticity in glioblastoma remain poorly understood. Here, using machine learning (ML) we employ cross-patient prediction of transcript expression using a combination of epigenetic features (ATAC-seq, CTCF ChIP-seq, RNAPII ChIP-seq, H3K27Ac ChIP-seq, and RNA-seq) of glioblastoma stem cells (GSCs). We investigate different ML and deep learning (DL) models for this task and build our final pipeline using XGBoost. The model trained on one patient generalizes to another one suggesting that the epigenetic signals governing gene transcription are consistent across patients even if GSCs can be very different. We demonstrate that H3K27Ac is the epigenetic feature providing the most significant contribution to cross-patient prediction of gene expression. In addition, using H3K27Ac signals from patients-derived GSCs, we can predict gene expression of human neural crest stem cells suggesting a shared developmental epigenetic trajectory between subpopulations of these malignant and benign stem cells.Our cross-patient ML/DL models determine weighted patterns of influence of epigenetic marks on gene expression across patients with glioblastoma and between GSCs and neural crest stem cells. We propose that broader application of this analysis could reshape our view of glioblastoma tumor evolution and inform the design of new epigenetic targeting therapies.
Intraperitoneal activation of myeloid cells clears ascites and reveals IL27-dependent regression of metastatic ovarian cancer
Authors: Murphy Brennah , Miyamoto Taito , Manning Bryan S. , Mirji Gauri , Ugolini Alessio , Kannan Toshitha , Hamada Kohei , Zhu Yanfang Peipei , Claiborne Daniel T. , Huang Lu , Zhang Rugang , Nefedova Yulia , Kossenkov Andrew , Veglia Filippo , Shinde Rahul , Zhang Nan 
Published: June 2024

AbstractPatients with metastatic ovarian cancer (OvCa) have a 5-year survival rate of less than 30% due to persisting dissemination of chemoresistant cells in the peritoneal fluid and the immunosuppressive microenvironment in the peritoneal cavity. Here, we report that intraperitoneal administration of β-glucan and IFNγ (BI) induced robust tumor regression in clinically relevant models of metastatic OvCa. BI induced tumor regression by controlling fluid tumor burden and activating localized antitumor immunity. β-glucan alone cleared ascites and eliminated fluid tumor cells by inducing intraperitoneal clotting in the fluid and Dectin-1-Syk-dependent NETosis in the omentum. In omentum tumors, BI expanded a novel subset of immunostimulatory IL27+ macrophages and neutralizing IL27 impaired BI efficacyin vivo. Moreover, BI directly induced IL27 secretion in macrophages where single agent treatment did not. Finally, BI extended mouse survival in a chemoresistant model and significantly improved chemotherapy response in a chemo-sensitive model. In summary, we propose a new therapeutic strategy for the treatment of metastatic OvCa.
The Role of Biopsy Position and Tumor-Associated Macrophages for Predictions on Recurrence of Malignant Gliomas: An In Silico Study
Authors: Shojaee Pejman , Weinholtz Edwin , Schaadt Nadine S. , Hatzikirou Haralampos 
Published: June 2024

AbstractPredicting the biological behavior and time to recurrence (TTR) of high-grade diffuse gliomas (HGG) after the maximum safe neurosurgical resection and combined radiation and chemotherapy plays a pivotal role in planning the clinical follow-up, the choice of potentially necessary second-line treatment, and the quality of life of patients faced with the diagnosis of a malignant brain tumor. The current standard-of-care (SoC) for HGG includes follow-up neuroradiological imaging to detect recurrence as early as possible and several clinical, neuropathological, and radiological prognostic factors with limited accuracy toward predicting TTR. Herein, using an in-silico analysis, we aim to improve predictive power towards TTR considering the role of (i) prognostically relevant information available by diagnostics used in current SoC, (ii) advanced image-based information that is currently not part of the standard diagnostic workup, such as interface of tumor and normal tissue (edge) features and quantitative data specific for the position of biopsies within the tumor, and (iii) information on tumor-associated macrophages. In particular, we introduce a state-of-the-art spatio-temporal model of tumor-immune interactions, emphasizing the interplay between macrophages and glioma cells. This model serves as a synthetic reality for assessing the predictive value of various features. We generate a cohort of virtual patients based on our mathematical model. Each patient’s dataset includes simulated T1 and FLAIR MRI volumes, and simulated results on macrophage density and proliferative activity either in a specified part of the tumor, namely tumor core or edge (”localized”), or unspecified (”non-localized”). We impose different levels of noise to enhance the realism of our synthetic data. Our findings reveal that macrophage density at the tumor edge contributes to a high predictive value of feature importance for the selected regression model. Moreover, there is a lower MSE and higherR2for the ”localized” biopsy in prediction accuracy toward recurrence post-resection compared with ”non-localized” specimens. In conclusion, the results show us that localized biopsies can bring more information about the tumor behavior, especially at the interface of tumor and normal tissue (Edge).
Network-Based Analysis Identifies Targetable Pathways in Comorbid Type II Diabetes and Neuropsychiatric Disorders
Authors: Onisiforou Anna , Zanos Panos 
Published: June 2024

AbstractComorbid diseases complicate patient outcomes and escalate healthcare costs, necessitating a deeper mechanistic understanding. Neuropsychiatric disorders (NPDs) such as Neurotic Disorder, Major Depression, Bipolar Disorder, Anxiety Disorder, and Schizophrenia significantly exacerbate Type 2 Diabetes Mellitus (DM2), often leading to suboptimal treatment outcomes. The neurobiological underpinnings of this comorbidity remain poorly understood. To address this, we developed a novel pathway-based network computational framework that identifies critical common disease mechanisms between DM2 and the five prevalent NPDs. Our approach involves reconstructing an integrated DM2 ∩ NPDs KEGG pathway network and applying two complementary analytical methods, including the “minimum path to comorbidity” method to identify the shortest pathways fostering comorbid development. This analysis uncovered shared pathways like the PI3K-Akt signaling pathway and highlighted key nodes such as calcium signaling, MAPK, estrogen signaling, and apoptosis pathways. The dysregulation of these pathways likely contributes to the development of DM2-NPDs comorbidity. Our model not only elucidates the intricate molecular interactions driving this comorbidity but also identifies promising therapeutic targets, paving the way for innovative treatment strategies. This framework can be adapted to study other complex comorbid conditions, offering broad implications for improving patient care.
Adaptive Container Service: a New Paradigm for Robust and Optimized Bioinformatics Workflow Deployment in the Cloud
Authors: Kang Kevin , Wo Jinwen , Jiang Jon , Wang Zhong 
Published: June 2024

AbstractWe propose Adaptive Container Service (ACS), a new paradigm for deploying bioinformatics workflows in cloud computing environments. By encapsulating the entire workflow within a single virtual container, combined with automatic workflow checkpointing and dynamic migration to appropriately scaled containers, ACS-based deployment demonstrates several key advantages over alternative strategies: it enables optimal resource provision to any workflow that comprise of multiple applications with diverse computing needs; it provides protection against application-agnostic out-of-memory (OOM) errors or spot instance interruptions; and it reduces efforts required for workflow development, optimization, and management because it runs workflows with minimal or no code modifications. Proof-of-concept experiments show that ACS avoided both under- and over-provisioning in monolithic single-container deployment. Despite being deployed as a single container, it achieved comparable resource utilization efficiency as optimized Nextflow-managed, multi-modular workflows. Analysis of over 18,000 workflow runs demonstrated that ACS can effectively reduce workflow failures by two-thirds. These findings suggest that ACS frees developers from navigating the complexity of deploying robust workflows and rightsizing compute resources in the cloud, leading to significant reduction in workflow development time and savings in cloud computing costs.
Medulloblastoma Spatial Transcriptomics Reveals Tumor Microenvironment Heterogeneity with High-Density Progenitor Cell Regions Correlating with High-Risk Disease
Authors: Chien Franklin , Michaud Marina E. , Bakhtiari Mojtaba , Schroff Chanel , Snuderl Matija , Velazquez Vega Jose E. , MacDonald Tobey J. , Bhasin Manoj K. 
Published: June 2024

AbstractThe tumor microenvironment (TME) of medulloblastoma (MB) influences progression and therapy response, presenting a promising target for therapeutic advances. Prior single-cell analyses have characterized the cellular components of the TME but lack spatial context. To address this, we performed spatial transcriptomic sequencing on sixteen pediatric MB samples obtained at diagnosis, including two matched diagnosis-relapse pairs. Our analyses revealed inter- and intra-tumoral heterogeneity within the TME, comprised of tumor-associated astrocytes (TAAs), macrophages (TAMs), stromal components, and distinct subpopulations of MB cells at different stages of neuronal differentiation and cell cycle progression. We identified dense regions of quiescent progenitor-like MB cells enriched in patients with high-risk (HR) features and an increase in TAAs, TAMs, and dysregulated vascular endothelium following relapse. Our study presents novel insights into the spatial architecture and cellular landscape of the medulloblastoma TME, highlighting spatial patterns linked to HR features and relapse, which may serve as potential therapeutic targets.
Bee microbiomes in a changing climate: investigating the effects of temperature on solitary bee life history and health
Authors: Crowley Bailey L. , Schaeffer Robert N. 
Published: June 2024

AbstractClimate change is rapidly warming thermal environments, an important abiotic stimulus governing bee development and species interactions. Increasing evidence suggests that solitary bees rely upon pollen provision microbes for successful development. The effects of heat stress on provision microbiota and resulting consequences for larval health and development, however, remain to be examined. We performed anin vitrostudy to investigate the effects of thermal environment on provision microbiome composition and measured fitness outcomes forOsmia lignarialarvae. Elevated temperatures moderately increased the mean rank relative abundance ofArsenophonus, a putative son-killing symbiont. While pollen sterilization removedArsenophonusfrom microbe-rich provisions, larval survivorship did not significantly differ between bees reared on microbe-rich and sterile diets. In contrast to previous research in solitary bees, larvae reared on sterile provisions weighed more and had higher total fat contents, with temperature moderating the degree of difference. As anticipated, we observed a negative relationship between the duration of larval development and temperature. Our results indicated that an intact provision microbiota may not always improve bee fitness, and that bee-microbe interactions during larval development may contribute to the size-shrinking effect observed for cavity-nesting bees under warming conditions.
In silico generation and augmentation of regulatory variants from massively parallel reporter assay using conditional variational autoencoder
Authors: Jin Weijia , Xia Yi , Thela Sai Ritesh , Liu Yunlong , Chen Li 
Published: June 2024

AbstractPredicting the functional consequences of genetic variants in non-coding regions is a challenging problem. Massively parallel reporter assays (MPRAs), which are anin vitrohigh-throughput method, can simultaneously test thousands of variants by evaluating the existence of allele specific regulatory activity. Nevertheless, the identified labelled variants by MPRAs, which shows differential allelic regulatory effects on the gene expression are usually limited to the scale of hundreds, limiting their potential to be used as the training set for achieving a robust genome-wide prediction. To address the limitation, we propose a deep generative model, MpraVAE, toin silicogenerate and augment the training sample size of labelled variants. By benchmarking on several MPRA datasets, we demonstrate that MpraVAE significantly improves the prediction performance for MPRA regulatory variants compared to the baseline method, conventional data augmentation approaches as well as existing variant scoring methods. Taking autoimmune diseases as one example, we apply MpraVAE to perform a genome-wide prediction of regulatory variants and find that predicted regulatory variants are more enriched than background variants in enhancers, active histone marks, open chromatin regions in immune-related cell types, and chromatin states associated with promoter, enhancer activity and binding sites of cMyC and Pol II that regulate gene expression. Importantly, predicted regulatory variants are found to link immune-related genes by leveraging chromatin loop and accessible chromatin, demonstrating the importance of MpraVAE in genetic and gene discovery for complex traits.
A large-scale optogenetic neurophysiology platform for improving accessibility in NHP behavioral experiments
Authors: Griggs Devon J. , Bloch Julien , Stanis Noah , Zhou Jasmine , Fisher Shawn , Jahanian Hesamoddin , Yazdan-Shahmorad Azadeh 
Published: June 2024

AbstractOptogenetics has been a powerful scientific tool for two decades, yet its integration with non-human primate (NHP) electrophysiology has been limited due to several technical challenges. These include a lack of electrode arrays capable of supporting large-scale and long-term optical access, inaccessible viral vector delivery methods for transfection of large regions of cortex, a paucity of hardware designed for large-scale patterned cortical illumination, and inflexible designs for multi-modal experimentation. To address these gaps, we introduce a highly accessible platform integrating optogenetics and electrophysiology for behavioral and neural modulation with neurophysiological recording in NHPs. We employed this platform in two rhesus macaques and showcased its capability of optogenetically disrupting reaches, while simultaneously monitoring ongoing electrocorticography activity underlying the stimulation-induced behavioral changes. The platform exhibits long-term stability and functionality, thereby facilitating large-scale electrophysiology, optical imaging, and optogenetics over months, which is crucial for translationally relevant multi-modal studies of neurological and neuropsychiatric disorders.Graphical Abstract
Stabilization of GTSE1 by cyclin D1-CDK4/6-mediated phosphorylation promotes cell proliferation: relevance in cancer prognosis
Authors: García-Vázquez Nelson , González-Robles Tania J. , Lane Ethan , Spasskaya Daria , Zhang Qingyue , Kerzhnerman Marc , Jeong YeonTae , Collu Marta , Simoneschi Daniele , Ruggles Kelly V. , Rona Gergely , Kaisari Sharon , Pagano Michele 
Published: June 2024

AbstractIn healthy cells, cyclin D1 is expressed during the G1 phase of the cell cycle, where it activates CDK4 and CDK6. Its dysregulation is a well-established oncogenic driver in numerous human cancers. The cancer-related function of cyclin D1 has been primarily studied by focusing on the phosphorylation of the retinoblastoma (RB) gene product. Here, using an integrative approach combining bioinformatic analyses and biochemical experiments, we show that GTSE1 (G-Two and S phases expressed protein 1), a protein positively regulating cell cycle progression, is a previously unrecognized substrate of cyclin D1-CDK4/6 in tumor cells overexpressing cyclin D1 during G1 and subsequent phases. The phosphorylation of GTSE1 mediated by cyclin D1-CDK4/6 inhibits GTSE1 degradation, leading to high levels of GTSE1 across all cell cycle phases. Functionally, the phosphorylation of GTSE1 promotes cellular proliferation and is associated with poor prognosis within a pan-cancer cohort. Our findings provide insights into cyclin D1’s role in cell cycle control and oncogenesis beyond RB phosphorylation.