bluuebunny/crossref_metadata_2025 huggingface dataset:
Vinculin Y822 phosphorylation regulates cardiomyocyte adhesion dynamics and adherens junction maturation in the heart
Authors: Li Xiaofei , Wortelboer Rainy , Song Yi , Balasubramanian Sahana , McLain Callie , Hernandez Manriquez Alex , Suh Joseph , Hoffman Brenton D. , Kwiatkowski Adam V. , Radice Glenn L.
Published: November 2024

In the heart, cell-matrix and cell-cell adhesions reorganize in response to increased cardiac demand and growth to promote cardiomyocyte maturation. Vinculin, a mechanosensitive adaptor protein, links filamentous actin to cell-matrix and cell-cell adhesions and is thus positioned to regulate adhesion reorganization. However, how the two adhesion systems are coordinated in the heart, and the role of vinculin in this process is poorly understood. Here, we define the role of vinculin phosphorylation at tyrosine residue 822 (pY822) in cardiomyocyte adhesion and heart function. We found that pY822 correlated with dynamic junction remodeling in the developing heart but was lost as junctions matured postnatally. We then mutated Y822 to phenylalanine (Y822F) in the mouse to determine pY822 function in vivo. Homozygous mutant Vcl Y822F mice were viable and exhibited normal cardiac function at ten weeks of age; however, cardiac dysfunction was observed at 28 weeks. Vinculin and adherens junction proteins were reduced at cardiomyocyte junctions in Y822F hearts. In contrast, α5/β1 integrin and fibronectin increased along the lateral border of Y822F cardiomyocytes. Our results demonstrate that vinculin Y822 phosphorylation regulates the balance between cadherin and integrin adhesion organization, highlighting the importance of post-translational modification in modulating vinculin function in heart physiology.
A unifying principle for multispecies coexistence under resource fluctuations
Authors: Richardson James A. , Engelstädter Jan , Letten Andrew D.
Published: November 2024

Resource fluctuations are ubiquitous in nature and yet are generally assumed to play a limited role in the maintenance of biodiversity. We challenge this assumption by analyzing resource competition dynamics under conditions where traditional theory fails. We show that multi-species coexistence can be sustained when species are able to specialise on different temporal patterns of resource variability, including the asymmetries and periodic extremes commonly observed in natural systems. We further show how this partitioning of the statistical moments of the resource distribution provides a unified framework for explaining coexistence in variable resource environments. A theory of diversity maintenance based on moment partitioning highlights the potential for anthropogenic changes in resource regimes to drive cascading biodiversity losses.
Reliable prediction of protein-protein binding affinity changes upon mutations with Pythia-PPI
Authors: Tao Fangting , Sun Jinyuan , Wu Bian , Gao George F
Published: November 2024

Protein-protein interactions are essential for numerous biological functions, and predicting binding affinity changes caused by mutations is crucial for understanding the impact of genetic variations and advancing protein engineering. Although machine learning-based methods show promise in improving the prediction accuracy, the scarcity of experimental data remains a significant bottleneck. Here, we utilized multi-task learning and self-distillation to overcome the data limitation and improved the accuracy of deep learning-based protein binding affinity prediction. By incorporating a mutation stability prediction task, the model achieved state-of-the-art accuracy on the SKEMPI dataset and was subsequently used to predict binding affinity changes for millions of mutations, generating an expanded dataset for self-distillation. Compared with prevalent methods, Pythia-PPI increased the Pearson correlation between predictions and experimental data from 0.6447 to 0.7850 on the SKEMPI dataset, and from 0.3654 to 0.6051 on the virial-receptor dataset. These findings demonstrated Pythia-PPI to be a valuable tool for analyzing the fitness landscape of protein-protein interactions. We provided a web server at https://pythiappi.wulab.xyz for easy access to Pythia-PPI.
Single-cell atlas of developing mouse palates reveals cellular and molecular transitions in periderm cell fate
Authors: Huang Wenbin , Qian Zhenwei , Zhang Jieni , Ding Yi , Wang Bin , Lin Jiuxiang , Zhang Xiannian , Zhao Huaxiang , Chen Feng
Published: November 2024

Cleft palate is one of the most common congenital craniofacial disorders that affects children’s appearance and oral functions. Investigating the transcriptomics during palatogenesis is crucial for comprehending the etiology of this disorder and facilitating prenatal molecular diagnosis. However, there is limited knowledge about the single-cell differentiation dynamics during mid- and late-palatogenesis, specifically regarding the subpopulations and developmental trajectories of periderm, a rare but critical cell population. Here we explore the single-cell landscape of mouse developing palates from E10.5 to E16.5. We systematically depict the single-cell transcriptomics of mesenchymal and epithelial cells during palatogenesis, including subpopulations and differentiation dynamics. Additionally, we identify four subclusters of palatal periderm and construct two distinct trajectories of cell fates for periderm cells. Our findings reveal thatClaudinsandArhgap29play a role in the non-stick function of the periderm before the palatal shelves contact, andPitx2mediates the adhesion of periderm during the contact of opposing palatal shelves. Furthermore, we demonstrate that epithelial-mesenchymal transition (EMT), apoptosis, and migration collectively contribute to the degeneration of periderm cells in the medial epithelial seam. Taken together, our study suggests a novel model of periderm development during palatogenesis and delineates the cellular and molecular transitions in periderm cell determination.
Platelets are Protective in Early Abdominal Aortic Aneurysm Formation
Authors: Russell Hannah M. , Spuzzillo Anthony R. , Benson Tyler W. , Jaworski James , Clément Marc , Boulaftali Yacine , Saum Keith , Conrad Kelsey A. , Howatt Deborah A. , Luyendyk James P. , Cameron Scott J. , Nieswandt Bernhard , Steinhubl Steven R. , Daugherty Alan , Bergmeier Wolfgang , Tong Wei , Damrauer Scott M. , Tsao Philip S. , Mallat Ziad , Edwards Todd L. , Mackman Nigel , Owens A. Phillip
Published: November 2024

Background

Abdominal aortic aneurysm (AAA) is a disease associated with the pathophysiologic degradation of the tunica media resulting in aortic dilatation, systemic inflammation, and dysregulated hemostasis. Beyond role its role in initiating primary hemostasis, platelets are a source of ROS, inflammatory cytokines and growth factors necessary for angiogenesis and vascular remodeling. Although platelets contribute to the progression of established aneurysms, their role in the initiation of AAA remains undefined.

Methods

Low density lipoprotein receptor deficient (Ldlr−/−) mice were examined for platelet accumulation in the angiotensin II (AngII) model of AAA utilizing in vivo labeling techniques. Two platelet antagonists (clopidogrel and aspirin), a thrombin inhibitor (dabigatran) or genetic deficiencies (protease-activated receptor 4,P2Y12,Lnk) were administered to AngII-infused mice to determine the role of platelets in initiation of AAA. The effect of platelet depletion was examined in multiple mouse strains of AngII-induced AAA and two additional aneurysm models. PheWAS and meta-analysis was analyzed in humans for platelet gene SNPs associated with AAA.

Results

We show that platelets are recruited rapidly to the aorta after the initiation of AngII infusion. Genetic deficiency of platelet receptors had no effect on abdominal aortic diameter, but augmented rupture-induced death in littermate versus placebo controls during AngII-induced AAA. Moreover,Ldlr−/−mice receiving anti-platelet inhibitors or a thrombin inhibitor also had augmented rupture-induced death. Platelet depletion preceding aneurysm formation resulted in pervasive rupture-induced death in several mouse strains and with three different mouse models of AAA.

Conclusions

Inhibition of platelet function is detrimental in an early expanding aortic lumen resulting in catastrophic rupture and hemodynamic failure in murine AAA models.
An Open Competition for Biomarkers of Aging
Authors: Ying Kejun , Paulson Seth , Reinhard Julian , de Lima Camillo Lucas Paulo , Träuble Jakob , Jokiel Stefan ,   Biomarkers of Aging Consortium, Gobel Dane , Herzog Chiara , Poganik Jesse R. , Moqri Mahdi , Gladyshev Vadim N.
Published: November 2024

Open scientific competitions have successfully driven biomedical advances but remain underutilized in aging research, where biological complexity and heterogeneity require methodological innovations. Here, we present the results from Phase I of the Biomarkers of Aging Challenge, an open competition designed to drive innovation in aging biomarker development and validation. The challenge leverages a unique DNA methylation dataset and aging outcomes from 500 individuals, aged 18 to 99. Participants are asked to develop novel models to predict chronological age, mortality, and multi-morbidity. Results from the chronological age prediction phase show important advances in biomarker accuracy and innovation compared to existing models. The winning models feature improved predictive power and employ advanced machine learning techniques, innovative data preprocessing, and the integration of biological knowledge. These approaches have led to the identification of novel age-associated methylation sites and patterns. This challenge establishes a paradigm for collaborative aging biomarker development, potentially accelerating the discovery of clinically relevant predictors of aging-related outcomes. This supports personalized medicine, clinical trial design, and the broader field of geroscience, paving the way for more targeted and effective longevity interventions.
PreDigs: a Database of Context-specific Cell-type Markers and Precise cell subtypes for Digestive Cell Annotation
Authors: Meng Jiayue , Han Mengyao , Huang Yuwei , Li Liang , Ju Yuanhu , Lv Daqing , Chen Xiaoyi , Yuan Liyun , Zhang Guoqing
Published: November 2024

Research on cell type markers aids investigators in exploring the diverse cellular compositions within gastrointestinal tumors, enhancing our understanding of tumor heterogeneity and its implications for disease progression and treatment response. However, issues such as the integration of large-scale datasets and the lack of standardized cell type identification hinder comprehensive characterization. Here, we developed a user-friendly web interface called PreDigs (Predicted Signatures in Digestive System), which offers 124 tailored scRNA-seq datasets available for download, encompassing over 3.4 million cells. After unsupervised clustering, we unified the identification and naming of subtype labels, ultimately constructing a cell ontology tree that includes 142 cell types, with up to eight hierarchical levels. Meanwhile, we calculated three different context-specific cell-type markers—’Cell Markers’, ‘Subtype Markers’, and ‘TPN Markers’—based on various application requirements within or across tissues. Through the integrated analysis of PreDigs gastrointestinal data, we identified distinct cell subpopulations exclusive to tumors, one of which corresponds to tumor-specific endothelial cells (TEC). Furthermore, PreDigs offers online cell annotation tools that empower users to perform single-cell classification with greater flexibility, accessible athttps://www.biosino.org/predigs/.
Salmonellaeffector SseL induces PD-L1 up-regulation and T cell inactivation via β-catenin signalling axis
Authors: Chopra Umesh , Sabu Maria Kondooparambil , Rajmani Raju S , Chaudhary Ayushi Devendrasingh , Gupta Shashi Kumar , Chakravortty Dipshikha
Published: November 2024

The upregulation of PD-L1 by various pathogens is a recognized strategy to evade the adaptive immune response.Salmonellainfection also upregulates PD-L1 levels causing culling of the activated T-cell; however, the underlying mechanism behind this upregulation is not known. Our findings indicate that the upregulation of PD-L1 is throughSalmonellapathogenicity island 2 (SPI-2) encoded effectors since PFA-fixed STM WT and STMΔssaV(which is unable to secrete effector proteins) did not alter PD-L1 levels. We have further investigated the role of the SPI-2 effector SseL (a deubiquitinase known to affect the NF-ĸB pathway) in PD-L1 upregulation. Our study identifies SPI-2 effector SseL to be crucial for upregulating PD-L1in vitroas well asin vivomurine models. The increase in PD-L1 levels induced by STM WT facilitates colonization in secondary infection sites in C57BL/6 mice, including the liver and spleen, while the STMΔsseLstrain exhibits significant colonization defects. Notably, despite the reduced colonization capacity of STMΔsseL, infected mice exhibit earlier mortality associated with heightened inflammation. We further elucidated the molecular mechanism behind PD-L1 upregulation and observed that bacterial effector SseL helps in the stabilization of β-catenin inside the cell. β-catenin thus translocates into the nucleus and directly regulates the transcriptional levels of PD-L1, which is abrogated upon using β-catenin/TCF inhibitor FH535. Collectively, our study elucidates the mechanism by whichSalmonellamediates immune suppression through PD-L1 upregulation.

Abstract Figure

Abstract figure: Schematic representation of SseL mediated PDL1 upregulation and further affecting the T cell proliferation
Phenotypic plasticity in a novel set of EGFR tyrosine kinase inhibitor-adapted non-small cell lung cancer cell lines
Authors: Nanthaprakash Tharsagini , Gourlay Campbell W. , Oehme Ina , Garrett Michelle D. , Cinatl Jindrich , Wass Mark N. , Michaelis Martin
Published: November 2024

Here, we introduce sublines of the EGFR-mutant non-small cell lung cancer (NSCLC) cell lines HCC827 and HCC4006 adapted to the EGFR kinase inhibitors gefitinib (HCC827rGEFI2µM, HCC4006rGEFI1µM), erlotinib (HCC827rERLO2µM, HCC4006rERLO1µM), and afatinib (HCC827rAFA50nM, HCC4006rAFA100nM). All sublines displayed resistance to gefitinib, erlotinib, afatinib, and the third-generation EGFR kinase inhibitor osimertinib that overcomes T790M-mediated resistance. HCC4006rERLO1µMdisplayed a spindle-like morphology in agreement with previous findings that had detected epithelial-mesenchymal-transition (EMT) in its precursor cell line HCC4006rERLO0.5µM. EMT had also been reported for the HCC4006rGEFI1µMprecursor cell line HCC4006rGEFI0.5µMand for HCC4006rAFA100nM, but the morphologies of HCC4006rGEFI1µMor HCC4006rAFA100nMdid not support this, suggesting plasticity in EMT regulation during the drug adaptation process and in established resistant cell lines. Accordingly, HCC4006rERLO1µMdisplayed resistance to MEK and AKT inhibitors in contrast to its precursor HCC4006rERLO0.5µM. We also detected metabolic plasticity, i.e., a temporary Warburg metabolism, in HCC4006 and HCC827rGEFI2µM. Response profiles to cytotoxic anti-cancer drugs, kinase inhibitors, and HDAC inhibitors resulted in complex patterns that were specific for each individual subline without obvious overlaps, indicating individual resistance phenotypes. All resistant sublines remained sensitive or displayed collateral sensitivity to at least one of the investigated drugs. In conclusion, the comparison of EGFR kinase-resistant NSCLC sublines with their precursor cell lines that had been previously characterised at a lower resistance level and metabolic investigations indicated phenotypic plasticity during the resistance formation process and in established cell lines. This plasticity may contribute to the well-known variability in cell line phenotypes observed between different laboratories and in intra-laboratory experiments.
PSTP: Decoding Latent Sequence Grammar for Protein Phase Separation through Transfer Learning and Attention
Authors: Feng Mofan , Liu Liangjie , Xian Zhuo-Ning , Wei Xiaoxi , Li Keyi , Yan Wenqian , Lu Qing , Shi Yi , He Guang
Published: November 2024

Phase separation (PS) is essential in various biological processes, necessitating high-accuracy predictive algorithms for studying numerous uncharacterized sequences, and accelerating experimental validation. However, many recent prediction methods face challenges in generalizability due to their reliance on engineered features. Furthermore, accurately identifying protein regions involved in PS remains challenging. To address this, we propose PSTP, a model employing a dual-language model embedding strategy and a lightweight attention module. The attention layer enables reliable residue-level phase separation predictions, identifying 84% of PS regions in PhaSePro and substantially improving correlation coefficient compared to existing models. PSTP also demonstrates robust performance in predicting PS propensity across various types of PS proteins and shows potential for predicting artificial proteins. By analyzing 160,000+ variants, PSTP characterizes the link between the incidence of pathogenic variants and residue-level PS propensities. PSTP’s predictive power and broad applicability make it a valuable tool for understanding biomolecular condensates and disease mechanisms.
The cold tolerance of the terrestrial slug,Ambigolimax valentianus
Authors: Gill Lauren T. , Udaka Hiroko , Marshall Katie E.
Published: November 2024

Terrestrial molluscs living in temperate and polar environments must contend with cold winter temperatures. However, the physiological mechanisms underlying the survival of terrestrial molluscs in cold environments and the strategies employed by them are poorly understood. Here we investigated the cold tolerance ofAmbigolimax valentianus, an invasive, terrestrial slug that has established populations in Japan, Canada, and Europe. To do this, we acclimatedA. valentianusto different environmental conditions (differing day lengths and temperatures), then exposed them to sub-zero temperatures and measured overall survival. Then, we measured low molecular weight metabolites using1H NMR to see if they play a role in their cold tolerance as they do in other invertebrate species. We found thatA. valentianusis not strongly freeze tolerant but do become more cold-hardy after acclimation to shorter day lengths. We also found that no metabolites were strongly upregulated in response to winter conditions despite the change in cold hardiness, and instead saw evidence of metabolic suppression leading up to winter such as formate and L-glutamine being supressed in winter conditions.
Bayesian modeling of mutual exclusivity in cancer mutations
Authors: Czyż Paweł , Beerenwinkel Niko
Published: November 2024

When cancer develops, gene mutations do not occur independently, prompting researchers to pose scientific hypotheses about their interactions. Synthetic lethal interactions, which result in mutually exclusive mutations, have received considerable attention as they may inform about the structure of aberrant biological pathways in cancer cells and suggest therapeutic targets. However, finding patterns of mutually exclusive genes is a challenging task due to small available sample sizes, sequencing noise, and confounders present in observational studies. Here, we leverage recent advancements in probabilistic programming to propose a fully Bayesian framework for modeling mutual exclusivity based on a family of constrained Bernoulli mixture models. By forming continuous model expansion within the iterative Bayesian workflow, we quantify the uncertainty resulting from small sample sizes and perform careful model criticism. Our analysis indicates that alterations in the EGFR and IDH1 genes may exhibit mutual exclusivity in glioblastoma multiforme tumors. We argue that Bayesian analysis offers a conceptual, systematic, and computationally feasible approach to model building, complementing the findings obtained from classical hypothesis testing approaches.
PAL-AI reveals genetic determinants that control poly(A)-tail length during oocyte maturation with relevance to human fertility
Authors: Xiang Kehui , Bartel David P.
Published: November 2024

In oocytes of mammals and other animals, gene regulation is mediated primarily through changes in poly(A)-tail length1–9. Here, we introduce PAL-AI, an integrated neural network machine-learning model that accurately predicts tail-length changes in maturing oocytes of frogs and mammals. We show that PAL-AI learned known and previously unknown sequence elements and their contextual features that control poly(A)-tail length, enabling it to predict tail-length changes resulting from 3ʹ-UTR single-nucleotide substitutions. It also predicted tail-length-mediated translational changes, allowing us to nominate genes important for oocyte maturation. When comparing predicted tail-length changes in human oocytes with genomic datasets of the All of Us Research Program10and gnomAD11we found that genetic variants predicted to disrupt tail lengthening are under negative selection in the human population, thereby linking mRNA tail lengthening to human female fertility.
Antigen-specific T cell immunotherapy by in vivo mRNA delivery
Authors: Su Fang-Yi , Siebart Jamison C. , Chan Ching S. , Wang Matthew Y. , Yao Xinyi , Trenkle Aaron Silva , Sivakumar Avanti , Su Melanie , Harandi Rustin , Shahrawat Neha , Nguyen Chi H. , Goenka Anshika , Mun Jinhee , Dhodapkar Madhav V. , Kwong Gabriel A.
Published: November 2024

Immunotherapy has shown promise for treating patients with autoimmune diseases or cancer, yet treatment is associated with adverse effects associated with global activation or suppression of T cell immunity. Here, we developed antigen-presenting nanoparticles (APNs) to selectively engineer disease antigen (Ag)-specific T cells byin vivomRNA delivery. APNs consist of a lipid nanoparticle core functionalized with peptide-major histocompatibility complexes (pMHCs), facilitating antigen-specific T cell transfection through cognate T cell receptor-mediated endocytosis. In mouse models of type 1 diabetes and multiple myeloma, APNs selectively deplete autoreactive T cells leading to durable control of glycemia, and engineer virus-specific T cells with anti-cancer chimeric antigen receptors (CARs), achieving comparable therapeutic outcome as virally transducedex vivoCAR. Overall, our work supports the use of APNs to engineer disease-relevant T cellsin vivoas Ag-specific immunotherapy for autoimmune disorders and cancer.
Improved pangenomic classification accuracy with chain statistics
Authors: Brown Nathaniel K. , Shivakumar Vikram S. , Langmead Ben
Published: November 2024

Compressed full-text indexes enable efficient sequence classification against a pangenome or tree-of-life index. Past work on compressed-index classification used matching statistics or pseudo-matching lengths to capture the fine-grained co-linearity of exact matches. But these fail to capture coarse-grained information about whether seeds appear co-linearly in the reference. We present a novel approach that additionally obtains coarse-grained co-linearity (“chain”) statistics. We do this without using a chaining algorithm, which would require superlinear time in the number of matches. We start with a collection of strings, avoiding the multiple-alignment step required by graph approaches. We rapidly compute multi-maximal unique matches (multi-MUMs) and identify BWT sub-runs that correspond to these multi-MUMs. From these, we select those that can be “tunneled,” and mark these with the corresponding multi-MUM identifiers. This yields an ℴ(r+n/d)-space index for a collection ofdsequences having a length-nBWT consisting ofrmaximal equal-character runs. Using the index, we simultaneously compute fine-grained matching statistics and coarse-grained chain statistics in linear time with respect to query length. We found that this substantially improves classification accuracy compared to past compressed-indexing approaches and reaches the same level of accuracy as less efficient alignmentbased methods.
PNPLA3-I148M is a Neomorph that Interferes with Two Primary Hepatic Triglyceride Clearance Pathways
Authors: Sherman David J. , Liu Lei , LaGory Edward L. , Fordstrom Preston , Pruitt Danielle , Barreda Jose , Xie Jiansong , Ferbas John , Rulifson Ingrid C. , Deshaies Raymond J.
Published: November 2024

A common variant ofPNPLA3, encoding PNPLA3-I148M, is the most significant genetic determinant of fatty liver disease worldwide. However, it is unclear precisely how PNPLA3-I148M drives disease risk. Here, we show that endogenous human PNPLA3-I148M impairs secretion of Apolipoprotein B (ApoB), the scaffolding protein of very low-density lipoproteins (VLDLs), from hepatocytes. This is not due to a generalized secretory pathway defect, nor is it equivalent to loss of function of PNPLA3. The VLDL secretory defect is conserved in mice expressing human I148M. Untargeted lipidomics reveal that I148M human cells are enriched in polyunsaturated fatty acid (PUFA)-containing triglycerides at the expense of PUFA-containing phosphatidylcholine, causing reduced membrane dynamics, concomitantly hindering biogenesis of secreted VLDLs. ApoB secretion is substantially rescued in I148M cells that overexpress ABHD5/CGI-58, an I148M binding partner that activates lipolysis by ATGL/PNPLA2 when not bound to I148M. Conversely, knocking down CGI-58 or PNPLA2 mimics I148M. We propose that neomorphic PNPLA3-I148M exacerbates fatty liver risk by simultaneously impeding two major CGI-58-dependent pathways for liver triglyceride clearance: lipolysis and secretion.
Embryonic Mast Cells Arise fromCpa3-expressing Precursors Independent of Granulocyte-Monocyte Progenitors
Authors: Ma Wei , Chen Huifang , Gao Fei , Zhao Han , Wu Ningbo , Zhang Shuangyan , Zhu Yiwen , Xu Zijian , Lan Yu , Liu Bing , Ye Youqiong , Liu Zhaoyuan , Ginhoux Florent , Su Bing
Published: November 2024

Most of the mast cells (MCs) in connective tissues, such as skin, are long-lived embryonic-derived immune cells that play important roles in host defense and various immunological diseases, including allergies. Their embryonic origin and ontogeny remain to be fully studied since several overlapping waves of embryonic hematopoiesis have been shown to give rise to these cells. Here, combining single-cell RNA sequencing and new genetic fate mapping models, we identified aCpa3-expressing population sequentially appearing in the yolk sac, fetal liver, and peripheral tissues which gives rise to dermal MCs during embryonic days 11.5 to 14.5. Using in vitro differentiation and in vivo transplant methods, we identified a Ter119−F4/80−CD45+CD117+CD16/32+CD135−CD115−Ly6C−CD34lopopulation as potential fetal liver MC precursors. Fate mapping withCpa3CreERT2andZbtb16CreERT2models, as well as the granulocyte-monocyte progenitor (GMP) modelsMs4a3CreandElaneCre, demonstrated that MCs arise fromCpa3+progenitors rather thanMs4a3+orElane+GMPs. A corresponding population with a similar developmental trajectory was also identified in human early yolk sac and fetal liver, suggesting a conserved MC developmental program across species. These findings delineate the detailed developmental path of MCs in embryos, permitting future functional studies in immunity and development.

Highlights

Cpa3-expressing cells in the yolk sac and fetal liver contain mast cell precursors

Cpa3CreERT2labels embryonic mast cells and their precursors

Embryonic mast cells arise throughCpa3+mast cell precursors, but notElane+/Ms4a3+GMPs

The seeding of MCPs to embryonic skin slows down after E14.5
Aboral cell types ofClytiaand coral larvae have shared features and link taurine to the regulation of settlement
Authors: Ramon-Mateu Julia , Ferraioli Anna , Teixidó Núria , Domart-Coulon Isabelle , Houliston Evelyn , Copley Richard R.
Published: November 2024

Planktonic larvae of many marine invertebrates settle on a suitable substrate and metamorphose into bottom-dwelling adults. Larval settlement is of considerable interest both for ecologists and for evolutionary biologists, who have proposed that anterior sensory systems for substrate selection provided the basis for animal brains. Nevertheless the cellular and molecular regulation of larval settlement, including in Cnidaria (corals, jellyfish, sea anemones, hydroids) is not well understood. We generated and compared anterior (aboral) transcriptomes and single-cell RNA-seq datasets from the planula larvae of three cnidarian species: the hydrozoan jellyfishClytia hemisphaerica,and the scleractinian coralsAstroides calycularisandPocillopora acuta. Integrating these datasets and characterizing aboral cell types, we defined a common cellular architecture of the planula aboral end, and identified clade-specific specializations in cell types, including unique aboral neural cells in theClytiaplanula and neurosecretory cell types with distinct molecular signatures in bothClytiaand coral planulae. Among common planula aboral features were genes implicated in taurine uptake and catabolism expressed in distinct specialized cell types. In functional assays, exogenous taurine inhibited settlement of bothClytiaandAstroidesplanulae. These findings define a detailed molecular and cellular framework of the planula aboral pole, and implicate localized taurine destruction in defining settlement competence.
Bacterial protein function prediction via multimodal deep learning
Authors: Muzio Giulia , Adamer Michael , Fernandez Leyden , Borgwardt Karsten , Avican Kemal
Published: November 2024

Bacterial proteins are specialized with extensive functional diversity for survival in diverse and stressful environments. A significant portion of these proteins remains functionally uncharacterized, limiting our understanding of bacterial survival mechanisms. Hence, we developed Deep Expression STructure (DeepEST), a multimodal deep learning framework designed to accurately predict protein function in bacteria by assigning Gene Ontology (GO) terms. DeepEST comprises two modules: a multi-layer perceptron that takes gene expression and location as input features, and a protein structure-based predictor. Within DeepEST, we integrated these modules through a learnable weighted linear combination and introduced a novel masked loss function to fine-tune the structure-based predictor for bacterial species. We showed that DeepEST strongly outperforms existing protein function prediction methods relying solely on amino acid sequence or protein structure. Moreover, DeepEST predicts GO terms for unclassified hypothetical proteins across 25 human bacterial pathogens, facilitating the design of experimental setups for characterization studies.
A Novel Cisplatin-Based Prodrug Inhibits Lysine Deacetylases, Suppresses Nucleotide Excision Repair, and Overcomes Resistance
Authors: Negev-Korem Ya’ara , Stern Esther , Golan-Berman Hadar , Heilbrun Elisheva , Karmakar Subhendu , Soroka Yoram , Frušić-Zlotkin Marina , Chen Ofer , Hassanain Hiba , Wald Ori , Gibson Dan , Kohen Ron , Adar Sheera
Published: November 2024

Cisplatin [cis-diamminedichloroplatinum(II)] is a widely used chemotherapeutic agent that induces cytotoxicity primarily through DNA damage, but drug resistance severely limits its efficacy and use. Cisplatin resistance is complex and multifactorial, involving DNA repair via nucleotide excision repair (NER), and overexpression of lysine deacetylases (KDACs), which reduce chromatin accessibility and alter transcription regulation. The combination of cisplatin and KDAC inhibitors has shown promise in improving treatment efficacy. This improved efficacy has been attributed to increased drug sensitivity due to higher chromatin accessibility, however, this hypothesis has not been validated. In this study, we synthesized a novel Pt(IV) derivative,cct-[Pt(NH3)2Cl2(VPA)(PhB)] (cPVP), which combines cisplatin and two KDAC inhibitors, phenyl butyrate and valproic acid. This triple-action prodrug enabled the simultaneous targeting of multiple cancer-related pathways. Compared to cisplatin, cPVP exhibited significantly enhanced damage formation and cytotoxicity. High-resolution mapping of cisplatin damage and repair, however, does not attribute the enhanced damage sensitivity to chromatin accessibility, but rather to increased drug uptake and inhibition of nucleotide excision repair. Moreover, cPVP treatment increased survival in a mouse mesothelioma model, and prevented the development of resistance to both cisplatin and itself in cancer cells. Our findings shed new light on the effect of KDAC inhibition on cisplatin treatment, and suggest that cPVP could serve as a promising alternative to cisplatin in the clinic.
Functionally Important Residues from Graph Analysis of Coevolved Dynamic couplings
Authors: Xu Manming , Dantu Sarath Chandra , Garnett James A , Bonomo Robert A , Pandini Alessandro , Haider Shozeb
Published: November 2024

The relationship between protein dynamics and function is essential for understanding biological processes and developing effective therapeutics. Functional sites within proteins are critical for activities such as substrate binding, catalysis, and structural changes. Existing computational methods for the predictions of functional residues are trained on sequence, structural and experimental data, but they do not explicitly model the influence of evolution on protein dynamics. This overlooked contribution is essential as it is known that evolution can fine tune protein dynamics through compensatory mutations, either to improve the proteins' performance or diversify its function while maintaining the same structural scaffold. To model this critical contribution, we introduce DyNoPy, a computational method that combines residue coevolution analysis with molecular dynamics (MD) simulations, revealing hidden correlations between functional sites. DyNoPy constructs a graph model of residue-residue interactions, identifies communities of key residue groups and annotates critical sites based on their roles. By leveraging the concept of coevolved dynamical couplings, residue pairs with critical dynamical interactions that have been preserved during evolution, DyNoPy offers a powerful method for predicting and analysing protein evolution and dynamics. We demonstrate the effectiveness of DyNoPy on SHV-1 and PDC-3, chromosomally encoded beta-lactamases linked to antibiotic resistance, highlighting its potential to inform drug design and address pressing healthcare challenges.
Integration of multi-level dental diversity links macro-evolutionary patterns to ecological strategies across sharks.
Authors: Zimm Roland , Tobias-Santos Vitoria , Goudemand Nicolas
Published: November 2024

Sharks are notorious for their exceptional dental diversity, which is frequently used as a proxy for ecological function. However, functional inferences from morphology need to consider morphological features across different organizational scales, from small cusplets to patterns at the level of the entire jaw. Here, we deploy a set of classic and novel morphometric approaches to quantify morphological features ranging from sub-dental features to whole dentitions within a large ensemble of species encompassing all extant orders of sharks. We then correlate these measures with habitat, feeding and body size traits and track their variation as a function of genetic distance, a measure of trait adaptability. Intriguingly, sharks tend to either explore tooth-level or dentition-level complexity, resulting in two distinct groups with key differences in tooth symmetry, graduality of heterodont change, and depth of habitat. Overall, we find that intermediate levels of resolution, namely monognathic heterodonty in comparison with dignathic heterodonty and tooth-level shape descriptors, show the strongest predictive power for ecological traits, while exhibiting low phylogenetic signal, which suggests a more dynamic adaptability on shorter evolutionary timescales. This raises macro-evolutionary interpretations about the evolvability of nested modular phenotypic structures, with likely important implications for paleo-ecological inferences from sequentially homologous traits.
Competition, precipitation and temperature shape deviations from scaling laws in the crown allometries of miombo woodlands
Authors: Yambayamba Arthur M. , Fischer Fabian J. , Jucker Tommaso
Published: November 2024

Scaling relationships between different axes of tree size, such as height, crown radius, crown depth and stem diameter, play a direct role in shaping forest structure and function. Theoretical models such as metabolic scaling theory postulate that they are optimized for biomechanical stability and hydraulic sap distribution. However, empirical data often show that such models are only good enough as first order approximations because they do not account for differences in species traits and environmental conditions where trees grow. Nevertheless, the vast majority of research has focused on temperate systems or tropical rainforests, so we continue to lack a full understanding of what factors shape allometries of trees in tropical dry forests. Here, we compile data on tree height, diameter, crown radius and depth from miombo woodlands across Zambia and use Bayesian hierarchical modelling framework to explore how allometric scaling relationships are shaped by climate and competition. Similar to previous studies, our results revealed that allometric scaling relationships deviate substantially from theoretical expectations. We found that competition, precipitation and temperature all affect crown allometric scaling relationships, with trees becoming more slender where neighbourhood competition was greater, while crowns were wider and deeper in warmer and wetter climates. Our study highlights how the structure and function of miombo woodlands is shaped by more than just water availability. Moreover, by developing improved crown allometric models for miombo woodlands, we provide new tools to aid the estimation of aboveground biomass and calibration of remote sensing products in these critically important dry forest ecosystems.
Evolutionary history and rhizosphere microbial community composition in domesticated hops (Humulus lupulus L.)
Authors: McElwee-Adame Alexandra , Esplin-Stout Raya , Mugoya Trevor , Vourlitis George , Welch Nautica , Afram Kayser , Jeshvaghane Maryam Ahmadi , Bingham Nathan , Dockter Alexis , Eslava Jacob , Gil Giovanni , Mergens Joshua , Mohamed Amran , Nguyen Tram , Noor Fatum , Salcedo Nathan , Sethuraman Arun
Published: November 2024

Humulus lupulus L., commonly known as hops, is a perennial crop grown worldwide and is well known for its pharmacological, commercial, and most importantly brewing applications. For hundreds of years, hops have undergone intense artificial selection with over 250 cultivated varieties being developed worldwide, all displaying differences in key characteristics such as bitter acid concentrations, flavor and aroma profiles, changes in photoperiod, growth, and pathogen/pest resistances. Previous studies have individually explored differences between cultivars, aiming to identify markers that can quickly and cost-effectively differentiate between cultivars. However, little is known about their evolutionary history and the variability in their associated rhizospheric microbial communities. Coupling phenotypic, genomic, and soil metagenomic data, our study aims to explore the global population structure and domestication history of 98 hops cultivars. Additionally, we assessed differences in growth rates, rates of viral infection, usage of dissolvable nitrogen, and soil microbial community compositions between US and non-US based cultivars. Contrary to previous studies, our study revealed that worldwide hop cultivars cluster into four primary subpopulations; Central European, English, and American ancestry as previously reported, and one new group, the Nobles, revealing further substructure amongst Central European cultivars. Modeling the evolutionary history of domesticated hops reveals an early divergence of the common ancestors of modern US cultivars around 2800 ybp, and more recent divergences with gene flow across English, Central European, and Noble cultivars, reconciled with key events in human history and migrations. Furthermore, cultivars of US origin were shown to overall outperform non-US cultivars in both growth rates and usage of dissolvable nitrogen and display novel microbial composition.
Hypoxia induces extensive protein and proteolytic remodeling of the cell surface in pancreatic adenocarcinoma (PDAC) cell lines
Authors: Lui Irene , Schaefer Katie , Kirkemo Lisa L. , Zhou Jie , Perera Rushika M. , Leung Kevin K. , Wells James A.
Published: November 2024

The tumor microenvironment (TME) plays a crucial role in cancer progression. Hypoxia is a hallmark of the TME and induces a cascade of molecular events that affects cellular processes involved in metabolism, metastasis, and proteolysis. In pancreatic ductal adenocarcinoma (PDAC), tumor tissues are extremely hypoxic. Here, we leveraged mass spectrometry technologies to examine hypoxia-induced alterations in the abundance and proteolytic modifications to cell surface and secreted proteins. Across four PDAC cell lines, we discovered extensive proteolytic remodeling of cell surface proteins involved in cellular adhesion and motility. Looking outward at the surrounding secreted space, we identified hypoxia-regulated secreted and proteolytically-shed proteins that are responsible for regulating the humoral immune and inflammatory response and an upregulation of proteins involved in metabolic processing and tissue development. Combining cell surface N-terminomics and secretomics to evaluate the cellular response to hypoxia enabled us to identify significantly altered candidate proteins which may serve as potential biomarkers and therapeutic targets in PDAC. Furthermore, this approach provides a blue print for studying dysregulated extracellular proteolysis in other cancers and inflammatory diseases.
Synaptic cleft geometry modulates NMDAR opening probability by tuning neurotransmitter residence time
Authors: Mesa M. Hernández , McCabe K. J. , Rangamani P.
Published: November 2024

1

Synaptic morphology plays a critical role in modulating the dynamics of neurotransmitter diffusion and receptor activation in interneuron communication. In this study, we investigated how variations in synaptic geometry, including curvature of the synaptic cleft, distance between the presynaptic and postsynaptic membranes, and the surface area-to-volume ratio of the cleft, influence glutamate diffusion and N-Methyl-D-Aspartate receptor (NMDAR) opening probabilities. We developed a stochastic model for receptor activation using reconstructions from realistic synaptic geometries. Our simulations revealed a substantial variability in NMDAR activation, highlighting the significant impact of synaptic structure on receptor dynamics. By exploring the interplay between curvature and surface area-to-volume ratio, we found that increasing the curvature of the synaptic membranes could compensate for reduced NMDAR activation when the synaptic cleft distance was large. We also found that non-parallel membrane configurations, particularly convex presynapses or concave postsynaptic densities (PSDs), maximize NMDAR activation via increased surface area-to-volume ratio, leading to prolonged glutamate residence and reduced leakage. Finally, introducing NMDAR clustering within the PSD significantly enhanced receptor activation across different geometric conditions and mitigated the effects of synaptic morphology on NMDAR opening probabilities. Our findings underscore the complex interplay between synaptic geometry and receptor dynamics, providing insights into how structural modifications can influence synaptic efficacy and plasticity.

2

Significance statement

This study demonstrates that synaptic morphology profoundly shapes neurotransmitter diffusion and NMDA receptor activation, directly impacting synaptic efficacy. Our model shows that factors like synaptic cleft curvature, membrane spacing, and surface area-to-volume ratio significantly influence receptor dynamics. Given the dynamic nature of dendritic spines, which change shape and size during synaptic plasticity, our findings illustrate how purely morphological changes in cleft structure can modulate interneuronal communication and signal strength.
Causal Effects of Herpesvirus-Associated Antibodies on Autoimmune neuroinflammatory diseases: Mendelian Randomization Study
Authors: Sun Shujun , Wen Yiyong , Pan Tang , Fan Xie , Jun Wen , Xu Anding
Published: November 2024

Background

Herpesvirus infections may trigger Autoimmune neuroinflammatory diseases (ANDs), but their causal role is uncertain. This study used Mendelian randomization (MR) to investigate the causal effects of herpesvirus antibodies on ANDs.

Methods

We assessed 22 herpesvirus antibodies and five ANDs—multiple sclerosis (MS), neuromyelitis optica (NMO), myasthenia gravis (MG), Guillain-Barr é syndrome (GBS), and chronic inflammatory demyelinating polyneuropathy (CIDP)—using five MR methods. MR-PRESSO, MR-Egger, and Cochran’s Q statistic identified pleiotropy and heterogeneity. Bonferroni correction set the significance threshold at P<4.545e-04. Validation used UK Biobank and FinnGen data, with meta-analysis for inconsistent results.

Results

Significant positive causal effects were found for Epstein-Barr virus encoded nuclear antigen-1 (EBV EBNA-1) (OR=3.009), EBV viral capsid antigen (VCA) p18 (OR=8.700), and human herpesvirus 7(HHV7) U14 (OR=3.359) antibody levels on MS risk, and HHV7 U14 (OR=10.641), Varicella zoster virus glycoprotein E and glycoprotein I(VZV gE and gI) (OR=17.220) antibody levels on NMO risk. VZV gE and gI (OR=2.542) antibodies increased MG risk, while EBV ZEBRA (OR=0.592)reduced MS risk. Negative effects of EBV EA-D and ZEBRA antibodies on NMO were also noted. Validation confirmed the effects of EBV EBNA-1, EBV VCA p18 antibodies on MS, and VZV gE and gI on antibody MG, while EBV ZEBRA and HHV7 U14 antibodies effects on MS were not validated.

Conclusions

The study suggests a causal link between specific herpesvirus antibodies and the risk of MS, NMO, and MG.
PIPENN-EMB: ensemble net and protein embeddings generalise protein interface prediction beyond homology
Authors: Thomas David P. G. , Garcia Fernandez Carlos M. , Haydarlou Reza , Feenstra K. Anton
Published: November 2024

Protein interactions are crucial for understanding biological functions and disease mechanisms, but predicting these remains a complex task in computational biology. Increasingly, Deep Learning models are having success in interface prediction. This study presents PIPENN-EMB which explores the added value of using embeddings from theProtT5-XLprotein language model. Our results show substantial improvement over the previously published PIPENN model for protein interaction interface prediction, reaching an MCC of 0.313 vs. 0.249, and AUC-ROC 0.800 vs. 0.755 on theBIO_DL_TEtest set. We furthermore show that these embeddings cover a broad range of ‘hand-crafted’ protein features in ablation studies. PIPENN-EMB reaches state-of-the-art performance on theZK448dataset for protein-protein interface prediction. We showcase predictions on 25 resistance-related proteins fromMycobacterium tuberculosis. Furthermore, whereas other state-of-the-art sequence-based methods perform worse for proteins that have little recognisable homology in their training data, PIPENN-EMB generalises to remote homologs, yielding stable AUC-ROC across all three test sets with less than 30% sequence identity to the training dataset, and even to proteins with less than 15% sequence identity.

Availability

Webserver, source code and datasets atwww.ibi.vu.nl/programs/pipennemb/