bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection
Authors: Centofanti Edoardo , Oyler-Yaniv Alon , Oyler-Yaniv Jennifer 
Published: October 2024

AbstractCell fate decisions, such as proliferation, differentiation, and death, are driven by complex molecular interactions and signaling cascades. While significant progress has been made in understanding the molecular determinants of these processes, historically, cell fate transitions were identified through light microscopy that focused on changes in cell morphology and function. Modern techniques have shifted towards probing molecular effectors to quantify these transitions, offering more precise quantification and mechanistic understanding. However, challenges remain in cases where the molecular signals are ambiguous, complicating the assignment of cell fate. During viral infection, programmed cell death (PCD) pathways, including apoptosis, necroptosis, and pyroptosis, exhibit complex signaling and molecular crosstalk. This can lead to simultaneous activation of multiple PCD pathways, which confounds assignment of cell fate based on molecular information alone. To address this challenge, we employed deep learning-based image classification of dying cells to analyze PCD in single Herpes Simplex Virus-1 (HSV-1)-infected cells. Our approach reveals that despite heterogeneous activation of signaling, individual cells adopt predominantly prototypical death morphologies. Nevertheless, PCD is executed heterogeneously within a uniform population of virus-infected cells and varies over time. These findings demonstrate that image-based phenotyping can provide valuable insights into cell fate decisions, complementing molecular assays.
Temporal multi-modal single-cell analyses reveal dynamic interactions of CAR-T cells with glioblastoma and targeting of antigen-negative neoplastic cells
Authors: Zhang Daniel Y. , Wang Xin , Sun Yusha , Cui Qi , Nelson Ernest , Zhang Zhijian , Huang Brian , Giles Josephine , Thokala Radhika , Connolly Daniel R. , Jacob Fadi , Wherry E John , Lucas Timothy , Chen H. Isaac , Shi Yanhong , Brem Steven , Binder Zev A. , Nasrallah MacLean P. , Salinas Ryan D. , O’Rourke Donald M. , Ming Guo-li , Song Hongjun 
Published: October 2024

SUMMARYCAR-T therapy is a promising new immunotherapy for cancers, but its efficacy for solid tumors requires improvement. A detailed understanding of the interplay between solid tumors and CAR-T cells is critical. Here we report temporal, multi-modal, single-cell profiling of patient-derived glioblastoma organoids with CAR-T treatment. We found that all tumor cell types responded to CAR-T cell activation and contributed to an initially anti-tumor, but subsequently pro-tumor and immune-inhibitory microenvironment, accompanied by CAR-T cell exhaustion. Unexpectedly, CAR-T treatment attenuated glioma stem-like states of both antigen-positive and antigen-negative neoplastic cells and reduced their proliferation via diffusible factors, including IFNγ. Analysis of samples from additional patients, including those in clinical trials, supported these findings. Our study reveals the dynamic interplay among different tumor cells and T cells in adaptive responses to immunotherapy and identifies previously unappreciated benefits of CAR-T therapy directly on antigen-negative neoplastic cells that may be leveraged to enhance therapeutic efficacy.
Unique cuticular morphology of a truly marine insect,Echinophthirius horridusvon Olfers, 1816 (Phthiraptera: Echinophthiriidae)
Authors: White Tucker , Mikó István 
Published: October 2024

AbstractEchinophthiriidae is a family of aquatic lice parasitizing aquatic carnivorans, each member distinguished by their uniquely modified, curved setae.Echinophthirius horridusis known to parasitize a wide range of phocid (earless) seals as opposed to exhibiting the more species-specific parasitism of other echinophthiriid lice. In this study, we use a combination of bright field microscopy, confocal laser scanning microscopy (CLSM), and line drawings to provide a detailed description of the general body setae ofE. horridusand discuss its possible significance as an adaptation to a marine lifestyle.
Stochastic Gene Expression in Auxin Signaling in the Floral Meristem ofArabidopsis thaliana
Authors: Kong Shuyao , Zhu Mingyuan , Roeder Adrienne H.K. 
Published: October 2024

ABSTRACTCells display striking stochasticity in gene expression, which plays an important role in development, disease, and regeneration. Previous studies have found stochastic gene expression in bacteria, yeast, and from constitutive promoters in Arabidopsis. However, most promoters are non-constitutive. Stochastic gene expression from non-constitutive promoters in a multicellular organism, especially those with key developmental roles, remains largely uncharacterized. Here, we report stochastic expression of auxin responsive genes in the Arabidopsis floral meristem, using promoter reporters of DR5,ARABIDOPSIS HISTIDINE PHOSPHOTRANSFER PROTEIN6(AHP6), andDNA BINDING WITH ONE FINGER5.8(DOF5.8). We found highly variable DR5 expression patterns among younger meristems. Such variability is not attributed to heterogeneity in auxin perception, but to downstream stochastic expression of DR5, mainly influenced by cell-intrinsic molecular noise. Expression ofAHP6andDOF5.8is also noisy, although their noise is lower and has distinct spatiotemporal patterns unlike DR5. Finally, we propose spatial averaging as a mechanism that buffers cellular gene expression noise, allowing the formation of robust global expression patterns. Our study reveals stochastic gene expression downstream of auxin signaling, a key developmental player. Thus, stochastic gene expression from non-constitutive promoters, including those involved in hormone signaling, is an ordinary part of multicellular life.
Evolution of g-Type Lysozymes in Metazoa: Insights into Immunity and Digestive Adaptations
Authors: Mukherjee Krishanu , Moroz Leonid L. 
Published: October 2024

AbstractExploring the evolutionary dynamics of lysozymes is critical for advancing our knowledge of adaptations in immune and digestive systems. Here, we characterize the distribution of a unique class of lysozymes known as g-type, which hydrolyze key components of bacterial cell walls. Notably, many basal metazoan groups, including ctenophores, sponges, and choanoflagellates (the sister group of Metazoa), lack g-type lysozymes. We reveal a mosaic distribution of these genes, particularly within lophotrochozoans/spiralians, suggesting the lateral gene transfer (LGT) events from predatory myxobacteria played a role in their acquisition, enabling specialized dietary and defensive adaptations. We further identify two major groups of g-type lysozymes based on their widespread distribution in gastropods. Despite their sequence diversity, these lysozymes maintain conserved structural integrity that is crucial for enzymatic activity, underscoring independent evolutionary pathways where g-type lysozymes have developed functionalities typically associated with different lysozyme types in other species. Specifically, usingAplysia californicaas a reference species, we identified three distinct g-type lysozyme genes: two are expressed in organs linked to both feeding and defense, and the third exhibits broader distribution, likely associated with immune functions. These findings advance our understanding of the evolutionary dynamics shaping the recruitment and mosaic functional diversification of these enzymes across metazoans, offering new insights into ecological physiology and physiological evolution as emerging fields.
Phylogeny-aware simulations suggest a low impact of unsampled lineages in the inference of gene flow during eukaryogenesis
Authors: Bernabeu Moisès , Manzano-Morales Saioa , Gabaldón Toni 
Published: October 2024

AbstractGene phylogenies are broadly used to analyse events of horizontal gene transfer, namely, their presence, the potential donor and acceptor lineages, and their relative timing. Recent phylogenomics analyses have reconstructed a relative chronology of gene acquisitions in the lineage leading to the eukaryotes, revealing waves of acquisition from different donors before and after the mitochondrial endosymbiosis. However, a recognised caveat is the potential biases introduced by the presence of incomplete taxon sampling resulting in so-called “ghost” lineages. Here, we assessed the robustness of the gene phylogeny-based branch length ratio method in the inference of the relative ordering of gene acquisition events during eukaryogenesis. We introduce a novel simulation framework that populates a known dated Tree of Life with plausible “ghost” lineages and simulates their gene transfers to the lineage leading to the last eukaryotic common ancestor. Our simulations suggest a generally low probability of misinterpreting the relative order of gene acquisitions from distinct ghost donors. However, we identify specific problematic phylogenetic placements where unsampled lineages are more likely to produce misleading results. Overall, our approach offers valuable guidance for the interpretation of future work on eukaryogenesis, and can be readily adapted to other evolutionary scenarios.
Single-Cell Data Integration and Cell Type Annotation through Contrastive Adversarial Open-set Domain Adaptation
Authors: Aminzadeh Fatemeh , Wu Jun , He Jingrui , Saberi Morteza , Vafaee Fatemeh 
Published: October 2024

AbstractSingle-cell sequencing technologies have enabled in-depth analysis of cellular heterogeneity across tissues and disease contexts. However, as datasets increase in size and complexity, characterizing diverse cellular populations, integrating data across multiple modalities, and correcting batch effects remain challenges. We present SAFAARI (Single-cell Annotation and Fusion with Adversarial Open-Set Domain Adaptation Reliable for Data Integration), a unified deep learning framework designed for cell annotation, batch correction, and multi-omics integration. SAFAARI leverages supervised contrastive learning and adversarial domain adaptation to achieve domain-invariant embeddings and enables label transfer across datasets, addressing challenges posed by batch effects, biological domain shifts, and multi-omics modalities. SAFAARI identifies novel cell types and mitigates class imbalance to enhance the detection of rare cell types. Through comprehensive benchmarking, we evaluated SAFAARI against existing annotation and integration methods across real-world datasets exhibiting batch effects and domain shifts, as well as simulated and multi-omics data. SAFAARI demonstrated scalability and robust performance in cell annotation via label transfer across heterogeneous datasets, detection of unknown cell types, correction of batch effects, and cross-omics data integration while leveraging available annotations for improved integration. SAFAARI’s innovative approach outperformed competing methods in both qualitative and quantitative metrics, offering a flexible, accurate, and scalable solution for single-cell analysis with broad applicability to diverse biological and clinical research questions.
Patterns of extreme outlier RNA expression in population data reveal sporadic over-activation of genes with co-regulated modules in subsets of individuals
Authors: Xie Chen , Künzel Sven , Zhang Wenyu , Hathaway Cassandra A. , Tworoger Shelley S. , Tautz Diethard 
Published: October 2024

AbstractBackgroundMost RNA-Seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier expression.ResultsOur study is based on multiple datasets, including outbred and inbred mice, humans from the GTEx dataset, differentDrosophilaspecies and single-nuclei sequencing experiments from human brain tissues. All show comparable general patterns of outlier expression. Different individuals can harbor very different numbers of outliers, with some individuals showing extreme numbers in only one out of several organs of the respective individual. A three-generation family analysis in mice was generated and analyzed for the inheritance of outlier patterns. We find that most extreme over-expressions are not inherited, i.e., appear to be sporadically generated in individuals. Still, co-regulated outlier expressions are identifiable in various gene groups, and some correspond with known pathways. Among the co-regulated genes with extreme outlier expression are also the hormone genes prolactin and growth hormone, both in mice and humans, for which we include also protein level data from human cohorts.ConclusionsWe show that outlier patterns of gene expression are a biological reality occurring universally across tissues and species. Most of the outlier expressions are spontaneous and not inherited. We discuss the possibility that the outlier patterns reflect edge of chaos effects that are expected for systems of non-linear interactions and feedback loops, such as gene regulatory networks.
FT-like genes in Cannabis and hops: sex specific expression and copy-number variation may explain flowering time variation
Authors: Dowling Caroline A. , Michael Todd P. , McCabe Paul F. , Schilling Susanne , Melzer Rainer 
Published: October 2024

AbstractCannabis sativais a fascinating, yet under-researched, species. To facilitate the global expansion ofC. sativacultivation a greater understanding of flowering time control is crucial. ThePEBPgene family consists of universal promoters and repressors of flowering, with homologs ofFLOWERING LOCUS T(FT) being highly conserved key regulators of flowering.FTencodes florigen, and balancing the florigen and anti-florigen signals is key for fine-tuning a crop’s flowering to local climatic conditions. Here, we provide an in-depth characterisation of thePEBPgene family inC. sativaand the closely related speciesH. lupulus.Phylogenetic analysis reveals expansion ofFTandTFL1/CENclades in the Cannabaceae. The retention of the duplicatedPEBPgenes likely has functional significance with divergent sequences and expression patterns hinting at signatures of sub-functionalisation. We speculate that duplicatedPEBPgenes have been crucial to the evolution of photoperiod insensitivity and sexually dimorphic flowering inC. sativaand harnessing the available genetic variation for these traits will be key for establishing this future crop.
The FIP 1.0 Data Set: Highly Resolved Annotated Image Time Series of 4,000 Wheat Plots Grown in Six Years
Authors: Roth Lukas , Boss Mike , Kirchgessner Norbert , Aasen Helge , Aguirre-Cuellar Brenda Patricia , Akiina Price Pius Atuah , Anderegg Jonas , Gajardo Castillo Joaquin , Chen Xiaoran , Corrado Simon , Cybulski Krzysztof , Keller Beat , Kortstee Stefan Göbel , Kronenberg Lukas , Liebisch Frank , Nousi Paraskevi , Oppliger Corina , Perich Gregor , Pfeifer Johannes , Yu Kang , Storni Nicola , Tschurr Flavian , Treier Simon , Volpi Michele , Zellweger Hansueli , Zumsteg Olivia , Hund Andreas , Walter Achim 
Published: October 2024

AbstractBackgroundUnderstanding genotype-environment interactions of plants is crucial for crop improvement, yet limited by the scarcity of quality phenotyping data. This data note presents the Field Phenotyping Platform 1.0 data set, a comprehensive resource for winter wheat research that combines imaging, trait, environmental, and genetic data.FindingsWe provide time series data for more than 4,000 wheat plots, including aligned high-resolution image sequences totaling more than 151,000 aligned images across six years. Measurement data for eight key wheat traits is included, namely canopy cover values, plant heights, wheat head counts, senescence ratings, heading date, final plant height, grain yield, and protein content. Genetic marker information and environmental data complement the time series. Data quality is demonstrated through heritability analyses and genomic prediction models, achieving accuracies aligned with previous research.ConclusionsThis extensive data set offers opportunities for advancing crop modeling and phenotyping techniques, enabling researchers to develop novel approaches for understanding genotype-environment interactions, analyzing growth dynamics, and predicting crop performance. By making this resource publicly available, we aim to accelerate research in climate-adaptive agriculture and foster collaboration between plant science and computer vision communities.
D-lactate derived from intestinal bacteria drives lysine D-lactylation to modulate transcription in liver cells
Authors: Zang Yong , Zhang Jianji , Xia Mingxin , Wang Aiyuan , Fan Zilong , Han Yanpu , Zhang Hui , Wang Siyu , Niu Ziping , Wu Jingya , Bai Xue , Tian Shanshan , Chen Chen , Zhai Guijin , Dong Hanyang , Hu Deqing , Cheng Zhongyi , Zhang Kai 
Published: October 2024

AbstractEmerging evidence indicates that the accumulated D-lactate (D-la) from intestinal bacteria induces diverse effects in human intestinal injury diseases. However, its regulatory mechanism and functional consequence remain unclear. Here, we show that the secreted D-la induces lysine D-lactylation (K-Dla) to modulate transcription in host cells. We uncover K-Dla in HepG2 cells stimulated by D-la fromE. colisecretions. Then, we confirm the occurrence of D-la-driven K-Dla by four orthogonal approaches. We further validate that the existence of K-Dla in organisms by detecting the mouse liver and human intestinal tissue. Besides, we demonstrate a SCOT1-catalyzed biosynthetic pathway of D-lactyl-CoA, serving as a key donor for K-Dla. Next, we identify the K-Dla landscape with 2895 sites and further suggest the regulation of histone K-Dla in transcription by MNase ChIP-seq and RNA-seq assays. Finally, we show the potential effect of K-Dla on inhibiting the hepatocellular carcinoma cell proliferation. In summary, we report that the secreted D-la can induce K-Dla to regulate transcription, providing a new insight into the function of D-la secreted by gut microbiota and the effect of protein chemical modifications induced by bacterial secretions.
Catalytic-dependent and independent functions of the histone acetyltransferase CBP promote pioneer factor-mediated zygotic genome activation
Authors: Marsh Audrey J. , Pirogov Sergei , Ruffridge Abby J. , Sajwan Suresh , Gibson Tyler J. , Hunt George , Kaur Yadwinder , Harrison Melissa M. , Mannervik Mattias 
Published: October 2024

SummaryImmediately after fertilization the genome is transcriptionally quiescent. Maternally encoded pioneer transcription factors reprogram the chromatin state and facilitate the transcription of the zygotic genome. InDrosophila, transcription is initiated by the pioneer factor Zelda. While Zelda-occupied sites are enriched with histone acetylation, a post-translational mark associated with activecis-regulatory regions, the functional relationship between Zelda and histone acetylation in zygotic genome activation remained unclear. We show that Zelda-mediated recruitment of the histone acetyltransferase CBP is essential for zygotic transcription. CBP catalytic activity is necessary for release of RNA Polymerase II (Pol II) into transcription elongation and for embryonic development. However, CBP also activates zygotic transcription independent of acetylation through Pol II recruitment. Neither acetylation nor CBP are required for the pioneering function of Zelda. Our data suggest that pioneer factor-mediated recruitment of CBP is a conserved mechanism required to activate zygotic transcription but that this role is separable from the function of pioneer factors in restructuring chromatin accessibility.
Exploring the Potential of Malvidin and Echiodinin as Probable Antileishmanial Agents ThroughIn SilicoAnalysis AndIn VitroEfficacy
Authors: Goyzueta-Mamani Luis Daniel , Pagliara Lage Daniela , Barazorda-Ccahuana Haruna Luz , Paco-Chipana Margot , Candia-Puma Mayron Antonio , Davila-Del-Carpio Gonzalo , Sobreira Galdino Alexsandro , Machado-de-Avila Ricardo Andrez , Cordeiro Giunchetti Rodolfo , D’Antonio Edward L. , Ferraz Coelho Eduardo Antonio , Chávez-Fumagalli Miguel Angel 
Published: October 2024

AbstractLeishmaniasis is a neglected tropical disease, caused by distinctLeishmaniaspecies, which have significant public health challenges due to treatment limitations such as toxicity, high cost, and drug resistance. This study explores thein vitropotential of Malvidin and Echioidinin as probable antileishmanial agents againstLeishmania amazonensis,L. braziliensis, andL. infantum, comparing their efficacy to Amphotericin B (AmpB), a standard drug. Malvidin was more potent than Echioidinin across all parasite stages and species. ForL. amazonensis, Malvidin’s inhibitory concentration (IC50) values were 197.71±17.20 µM and 258.07±17 µM (stationary and axenic amastigotes, respectively); whereas Echioidinin revealed IC50values of 272.99±29.90 μM and 335.96±19.35 μM (stationary and axenic amastigotes, respectively). AmpB showed IC50values of 0.06±0.01 µM and 0.10±0.03 µM, respectively. Malvidin demonstrated lower cytotoxicity activity in mammalian cells with a cytotoxic concentration (CC50) value of 2,920.31±80.29 µM, while AmpB’s showed a value of 1.06±0.12 µM. Malvidin also exhibited favorable selectivity index (SI) values. Malvidin reduced infection rates by up to 35.75% inL. amazonensis-infected macrophages.In silicoanalysis uncovered strong binding interactions between Malvidin and enzyme arginase in the three species, with key residues such as HIS139 and PRO258 playing a crucial role. Tissue-specific markers expression analysis highlighted the potential Malvidin’s modulation of genes involved in oxidative stress and DNA repair, including glyoxalase 1 (GLO1) and apurinic/apyrimidinic endodeoxyribonuclease 1 (APEX1). Thein vitroandin silicodata corroborate the hypothesis that Malvidin is safe and can control theLeishmaniaparasites as a new natural compound for treatment. To further assess its therapeutic potential,in vivostudies are required to evaluate Malvidin’s efficacy, safety, and pharmacokinetics in animal models, which will be essential for validating its role as a candidate for leishmaniasis treatment.
Suspended Tissue Open Microfluidic Patterning (STOMP)
Authors: Haack Amanda J. , Brown Lauren G. , Goldstein Alex J. , Mulimani Priti , Berthier Jean , Viswanathan Asha R. , Kopyeva Irina , Whitten Jamison M. , Lin Ariel , Nguyen Serena H. , Leahy Thomas P. , Bouker Ella E. , Padgett Ruby M. , Mazzawi Natalie A. , Tokihiro Jodie C. , Bretherton Ross C. , Wu Aaliyah , Tapscott Stephen J. , DeForest Cole A. , Popowics Tracy E. , Berthier Erwin , Sniadecki Nathan J. , Theberge Ashleigh B. 
Published: October 2024

ABSTRACTCell-laden hydrogel constructs suspended between pillars are powerful tools for modeling tissue structure and physiology, though current fabrication techniques often limit them to uniform compositions. In contrast, tissues are complex in nature with spatial arrangements of cell types and extracellular matrices. Thus, we present Suspended Tissue Open Microfluidic Patterning (STOMP), which utilizes a removable, open microfluidic patterning channel to pattern multiple spatial regions across a single suspended tissue. The STOMP platform contains capillary pinning features along the open channel that controls the fluid front, allowing multiple cell and extracellular matrix precursors to be pipetted into one tissue. We have used this technique to pattern suspended tissues with multiple regional components using a variety of native and synthetic extracellular matrices, including fibrin, collagen, and poly(ethylene glycol). Here, we demonstrate that STOMP models a region of fibrosis in a functional heart tissue and a bone-ligament junction in periodontal tissues. Additionally, the STOMP platform can be customized to allow patterning of suspended cores and more spatial configurations, enhancing its utility in complex tissue modeling. STOMP is a versatile technique for generating suspended tissue models with increased control over cell and hydrogel composition to model interfacial tissue regions in a suspended tissue.