bluuebunny/crossref_metadata_2025_split huggingface dataset:
Benchmarking of T-Cell Receptor - Epitope Predictors with ePytope-TCR
Authors: Drost Felix , Chernysheva Anna , Albahah Mahmoud , Kocher Katharina , Schober Kilian , Schubert Benjamin 
Published: November 2024

AbstractUnderstanding the recognition of disease-derived epitopes through T-cell receptors (TCRs) has the potential to serve as a stepping stone for the development of efficient immunotherapies and vaccines. While a plethora of sequence-based prediction methods for TCR-epitope binding exists, their available pre-trained models have not been comparatively evaluated on standardized datasets and evaluation settings. Furthermore, technical problems such as non-standardized input and output formats of these prediction tools hinder interoperability and broad usage in applied research. To alleviate these shortcomings, we introduce ePytope-TCR, an extension of the vaccine design and immuno-prediction framework ePytope. We integrated 18 TCR-epitope prediction methods into this common framework offering interoperable interfaces with standard TCR repertoire data formats. We showcase the applicability of ePytope-TCR by evaluating the performance of the prediction methods on two challenging datasets for annotating single-cell repertoires and predicting TCR cross-reactivity towards mutated epitopes. While novel predictors successfully predicted binding to frequently observed epitopes, all methods failed for less observed epitopes. Further, we detected a strong bias in the prediction scores between different epitope classes. We envision this benchmark to guide researchers in their choice of a predictor for a given setting. Further, we aspire to accelerate the development of novel prediction models by allowing fast benchmarking against existing approaches through common interfaces and defining standardized evaluation settings.
SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data
Authors: Uhl Mathieu , Navascués Miguel , Boitard Simon , Servin Bertrand 
Published: November 2024

SummaryGenomic samples collected from a single population over several generations provide direct access to the genetic diversity changes occurring within a specific time period. This provides information about both demographic and adaptive processes acting on the population during that period. A common approach to analyze such data is to model observed allele counts in finite samples using a Hidden Markov model (HMM) where hidden states are true allele frequencies over time (i.e. a trajectory). The HMM framework allows to compute the full likelihood of the data, while accounting both for the stochastic evolution of population allele frequencies along time and for the noise arising from sampling a limited number of individuals at possibly spread out generations. Several such HMM methods have been proposed so far, differing mainly in the way they model the transition probabilities of the Markov chain. Following Paris et al. (2019a), we consider here the Beta with Spikes approximation, which avoids the computational issues associated to the Wright-Fisher model while still including fixation probabilities, in contrast to other standard approximations of this model like the Gaussian or Beta distributions. To facilitate the analysis and exploitation of genomic time series data, we present an improved version of Paris et al. (2019a) ‘s approach, denoted SelNeTime, whose computation time is drastically reduced and which accurately estimates effective population size in addition to the selection intensity at each locus. This method is implemented in a user friendly python package, which also allows to easily simulate genomic time series data under a user-defined evolutionary model and sampling design.
Ophiostomatoid fungi associated with bark beetles infestingPinus armandii, with characterizations of seven new species from China
Authors: Chen Minjie , Ran Yutong , Liu Congwang , Liu Kun , Lin Tong , Yin Mingliang 
Published: November 2024

AbstractOphiostomatoid fungi mainly refer to the order Ophiostomatales (Ascomycota), which are known to be symbiotic with bark beetles infesting pine trees. These fungi are primarily associated withDendroctonus armandiand other bark beetles, significantly impacting the local pinesPinus armandiiin western China. However, this fungal diversity must be further explored. This study aims to identify Ophiostomatoid fungi associated withP. armandiiin Ningshaan, Shaanxi Province. A total of 225 Ophiostomatalean isolates were obtained from 46 gallery samples, accounting for 77.6 % of the total number of isolated strains. Twenty species were identified based on the phylogenetic analyses of ITS, LSU, β-tubulin, and EF-1α, as well as morphological characteristics. These include seven new taxa,Ceratocystiopsis rugosa,Graphilbum prolificum,G. ramosus,Masuyamyces huoditangensis,Ophiostoma flavescens,O. lenta,O. mediotumida, and thirteen known species. This study laid a theoretical foundation for understanding the relationship between the beetles and the ophiostomatalean fungi in the Ningshan region, China.
Modeling Oncolytic Vaccinia Virus Therapy Highlights Neutrophil Impact on Tumor Suppression∗
Authors: Satani Sahaj , Dobrovolny Hana 
Published: November 2024

AbstractOncolytic vaccinia viruses (OVVs) present a promising approach for melanoma treatment due to their ability to selectively infect and lyse tumor cells. In this study, we use an ordinary differential equation (ODE) model of tumor growth inhibited by OVV activity to parameterize previous research on the effect of neutrophil depletion in B16-F10 melanoma tumors in mice. We find that the data are best fit by a model that accounts for neutrophil-mediated viral clearance, and that neutrophil depletion provides a mechanism for enhanced OVV efficacy and tumor reduction. We also find that parameter estimates for the most effective OVV regime share characteristics, most notably a low viral clearance rate by neutrophils, that might explain the improved outcomes. Further studies examining the impact of neutrophil modulation across different tumor models may help elucidate the extent to which these findings generalize and inform the design of novel OVV-based cancer therapies.
JOnTADS: a unified caller for TADs and stripes in Hi-C data
Authors: Zeng Qiuhai , Xiang Guanjue , Zhang Yu , Hardison Ross C. , Li Qunhua 
Published: November 2024

AbstractTopologically associating domains (TADs) and stripes are important architectural structures on Hi-C data that are important for gene regulation. We present Joint Optimized nested TADs and Stripes (JOn-TADS), a unified caller for TADs and stripes in Hi-C data. JOnTADS effectively identifies hierarchical TADs and stripes in population Hi-C and micro-C datasets, and hierarchical TADs in single-cell Hi-C data. It provides robust identifications aligned with known biology and effectively captures interaction frequency variations in contact maps across diverse contexts. When multiple samples are available, JOn-TADS leverages shared information across samples in TAD identification, reducing unwanted variation in TAD boundary identification while preserving biological differences. This approach enables robust identifications in single-cell Hi-C data, effectively addressing challenges posed by data sparsity. JOnTADS is computationally efficient and requires minimal user tuning.
CosinorTest: An R Shiny App for Cosinor-model-based circadian and differential analysis in transcriptomic applications
Authors: Ding Haocheng , Zhang Yutao , Meng Lingsong , Xing Chengguo , Esser Karyn A. , Huo Zhiguang 
Published: November 2024

AbstractSummary‘CosinorTest’ application is an interactive R Shiny tool designed to facilitate circadian and differential circadian analysis with transcriptomic data using Cosinor-model-based methods. This novel application integrates multiple major statistical algorithms to identify circadian rhythmicity in gene expression data and enables the comparison of differential circadian patterns between two experimental conditions. Key features of the ‘CosinorTest’ app include circadian rhythmicity detection, differential patterns assessment, circadian and differential analyses with repeated measurement, and interactive data visualization, all contributing to a comprehensive understanding of underlying biological mechanisms. As the application doing all comprehensive circadian analysis using the Cosinor model, the ‘CosinorTest’ app fills a crucial gap in the field of circadian biology and transcriptomics, providing a powerful and user-friendly platform for researchers, especially those without profound programming skills to explore the circadian gene expression regulation, and further advance circadian research.Availability and implementationCosinorTest is freely available athttps://circadiananalysis.shinyapps.io/circadianapp/.Contacthading@augusta.eduSupplementary informationSupplementary files are available atbioRχivonline.
ENaC contributes to macrophage dysfunction in cystic fibrosis
Authors: Moran John , Pugh Courtney , Brown Nevian , Thomas Ashley , Zhang Shuzhong , McCauley Emily , Cephas Amelia , Shrestha Chandra L. , Partida-Sanchez Santiago , Bai Shasha , Bruscia Emanuela , Kopp Benjamin T. 
Published: November 2024

ABSTRACTBackgroundCystic fibrosis (CF) is a chronic systemic disease caused by dysfunctional or absent cystic fibrosis transmembrane conductance regulator (CFTR). CFTR is expressed in human immune cells and plays a role in regulating innate immunity both directly and indirectly. Besides CFTR, research indicates that the epithelial sodium channel (ENaC) also contributes to dysfunction in CF airway epithelial cells. However, the impact of non-CFTR ion channel dysfunction on CF immune responses is not yet fully understood. A precise understanding of how CF immune function is regulated by ion channels may allow antibiotic-and mutation-agnostic treatment approaches to chronic bacterial infection and inflammation. Therefore, we hypothesized that ENaC is aberrantly expressed in CF macrophages and directly contributes to impaired phagocytic and inflammatory functions.MethodsENaC expression was characterized in human immune cells isolated from CF and non-CF blood donors. Monocyte-derived macrophage (MDM) function and bacterial killing was tested in the setting of ENaC modulation.ResultsBaseline expression of ENaC in human CF MDMs, lymphocytes, and granulocytes was increased at both the transcript and protein level relative to non-CF controls and persisted after exposure to bacteria. Inhibition of CFTR in non-CF MDMs resulted in ENaC overexpression.CFTR modulator treatment reduced but did not eliminate ENaC overexpression in CF MDMs. Interestingly, ENaC inhibition with Amiloride increased CFTR expression. Amiloride-treated CF MDMs also showed normalized ROS production, improved autophagy, and decreased pro-inflammatory cytokine production. Finally, results from an ion channel microarray indicated that sodium channel expression in CF MDMs normalized after Amiloride treatment with minimal effect on other ion channels.DiscussionENaC is overexpressed in CF immune cells and is associated with abnormal macrophage function. ENaC modulation in immune cells is a novel potential therapeutic target for infection control in CF, either in combination with CFTR modulators, or as a sole agent for patients not currently eligible for CFTR modulators.
Backward collateral sensitivity can restore antibiotic susceptibility
Authors: Chowdhury Farhan R. , Findlay Brandon L. 
Published: November 2024

AbstractThe prevalence of antibiotic resistance continues to rise, rendering many valuable drugs ineffective. Antibiotic cycling regimens that incorporate collateral sensitivity (CS), the phenomenon where resistance to one antibiotic leads to hypersensitivity to another, are hypothesized to slow the evolution of antibiotic resistance. However, the repeatability of CS interactions and their ability to drive bacterial extinction and resensitizations remain unclear. In this study, we thoroughly investigate four drug pairs proposed for cycling regimens with experimental evolution. We find that reported pairwise CS interactions are not always robust, and even when they are, forward CS (where resistance to drug A leads to hypersensitivity to drug B) does not reliably reduce resistance or promote bacterial extinction. Instead, we find that if evolution of resistance to drug B in naive cells is associated with CS to drug A, a phenomenon we term backward CS, drug A-resistant cells can be rendered more sensitive to A again when resistance to B develops. We describe the mechanism of resistance disruption via backward CS in an aminoglycoside-β-lactam pair, where perturbation of the electron transport chain to inhibit aminoglycoside entry impairs β-lactam efflux. Overall, we highlight the importance of applying antibiotics in the correct order in cycling regimens and identify robust CS interactions that may be used to design treatment regimens less likely to lead to resistance evolution.TOC Graphic
Altered basal forebrain regulation of intrinsic brain networks in depressive and anxiety disorders
Authors: Jamieson Alec J. , Steward Trevor , Davey Christopher G , Ince Sevil , Agathos James A , Moffat Bradford A , Glarin Rebecca K , Felmingham Kim L , Harrison Ben J 
Published: November 2024

AbstractAltered connectivity both within and between the default mode and salience networks have been observed across depressive and anxiety disorders. Recent work has highlighted the importance of subcortical regions, including subdivisions of the basal forebrain, in coordinating the activity of these networks. However, the precise influence of basal forebrain subregions on intrinsic networks across these disorders remains unknown. Using ultra-high field (7-Tesla) functional magnetic resonance imaging, we examined the resting-state effective connectivity of three basal forebrain subregions in a transdiagnostic sample of 70 individuals with mental health conditions, predominantly depressive and anxiety disorders, compared to 77 healthy controls. We explored connectivity between these subregions and regions of the salience network (anterior insula and dorsal anterior cingulate) and default mode network (ventromedial prefrontal cortex, posterior cingulate cortex, and inferior parietal lobule). Clinical participants showed increased inhibitory connectivity from the nucleus basalis of Meynert to regions of the default mode network and dorsal anterior cingulate. Increased inhibitory connectivity was also observed from the ventral pallidum to regions of the posterior default mode network. These transdiagnostic changes in the basal forebrain’s regulation of large-scale cortical networks across may suggest novel mechanistic avenues for pharmacological treatments, including cholinergic system targeting.
RNApysoforms: Fast rendering interactive visualization of RNA isoform structure and expression in Python
Authors: Heberle Bernardo Aguzzoli , Page Madeline L. , Gustavsson Emil K. , Ryten Mina , Ebbert Mark T. W. 
Published: November 2024

AbstractMotivationAlternative splicing generates multiple RNA isoforms from a single gene, enriching genetic diversity and impacting gene function. Effective visualization of these isoforms and their expression patterns is crucial but challenging due to limitations in existing tools. Traditional genome browsers lack programmability, while other tools offer limited customization, produce static plots, or cannot simultaneously display structures and expression levels. RNApysoforms was developed to address these gaps by providing a Python-based package that enables concurrent visualization of RNA isoform structures and expression data. Leveraging plotly and polars libraries, it offers an interactive, customizable, and faster-rendering framework suitable for web applications, enhancing the analysis and dissemination of RNA isoform research.Availability and implementationRNApysoforms is a Python package available at (https://github.com/UK-SBCoA-EbbertLab/RNApysoforms) via an open-source MIT license. It can be easily installed using the piip package installer for Python. Thorough documentation and usage vignettes are available at:https://rna-pysoforms.readthedocs.io/en/latest/.
The genome of the sapphire damselfishChrysiptera cyanea: a new resource to support further investigation of the evolution of Pomacentrids
Authors: Gairin Emma , Miura Saori , Takamiyagi Hiroki , Herrera Marcela , Laudet Vincent 
Published: November 2024

AbstractThe number of high-quality genomes is rapidly growing across taxa. However, it remains limited for coral reef fish of the Pomacentrid family, with most research focused on anemonefish. Here, we present the first assembly for a Pomacentrid of the genusChrysiptera. Using PacBio long-read sequencing with a coverage of 94.5x, the genome of the Sapphire Devil,Chrysiptera cyaneawas assembled and annotated. The final assembly consisted of 896 Mb pairs across 91 contigs, with a BUSCO completeness of 97.6%. 28,173 genes were identified. Comparative analyses with available chromosome-scale assemblies for related species identified contig-chromosome correspondences. This genome will be useful to use as a comparison to study the specific adaptations linked to symbiosis life of the closely related anemonefish. Furthermore, this species is present in most tropical coastal areas in the Indo-West Pacific and could become a model for environmental monitoring. This work will allow to expand coral reef research efforts and highlights the power of long-read assemblies to retrieve high quality genomes.
GCTransNet: 3D mitochondrial instance segmentation based on Global Context Vision Transformers
Authors: Chen Chaoyi , Yan Yidan , Wu Jingpeng , Gan Wen-Biao 
Published: November 2024

ABSTRACTMitochondria are double membrane-bound organelles essential for generating energy in eukaryotic cells. Mitochondria can be readily visualized in 3D using Volume Electron Microscopy (vEM), and accurate image segmentation is vital for quantitative analysis of mitochondrial morphology and function. To address the challenge of segmenting small mitochondrial compartments in vEM images, we propose an automated mitochondrial segmentation method called GCTransNet. This method employs grayscale migration technology to preprocess images, effectively reducing intensity distribution differences across EM images. By utilizing 3D Global Context Vision Transformers (GC-ViT) combined with global context self-attention modules and local self-attention modules, GCTransNet precisely models long-range and short-range spatial interactions. The long-range interactions enable the model to capture the global structural relationships within the mitochondrial segmentation network, while the short-range interactions refine local details and boundaries. In our approach, the encoder of the 3D U-Net network, a classical multi-scale learning architecture that retains high-resolution features through skip connections and combines multi-scale features for precise segmentation, is replaced by a 3D GC-ViT. The GC-ViT leverages shifted window-based self-attention, capturing long-range dependencies and offering improved segmentation accuracy compared to traditional U-Net encoders. In the MitoEM mitochondrial segmentation challenge, GCTransNet achieved state-of-the-art results, demonstrating its superiority in automated mitochondrial segmentation. The code and its documentation are publicly available athttps://github.com/GanLab123/GCTransNet.
Amyloid signaling in antiphage defense
Authors: Ibarlosa Léa , Dheur Sonia , Sanchez Corinne , Deb Seamoon , Granger-Farbos Alexandra , Coustou Virginie , Berbon Mélanie , Massoni Aurélie , Salin Bénédicte , Blancard Corinne , Saragaglia Claire , Tene Xavière Menatong , Dufour Nicolas , Rossier Ombeline , Habenstein Birgit , Debarbieux Laurent , Kauffmann Brice , Loquet Antoine , Saupe Sven J. 
Published: November 2024

AbstractImmune regulated cell death (RCD) is a defense strategy common to different domains of life involving purposeful sacrifice of infected cells. In animals and fungi, functional amyloids play a role in the control of RCD as molecular switches activating key cell death effectors, rather than causing direct toxicity as seen with pathological amyloids. Here, we describe a novel amyloid-based signal transduction mechanism in an antiphage defense system inEscherichia coli. This antiphage abortive infection (Abi) system is mediated by two proteins, Bab and Agp which share a common amyloid motif and are encoded by adjacent genes. Upon phage infection, Agp activates Bab through amyloid signaling, leading to cell death. We determined the structure of the Bab cell death execution domain, which is distantly related to pore-forming domains present in fungi, animals and plants. We show that Bab and the fungal HET-S amyloid-controlled cell death execution protein are functionally interchangeable in their respective roles in antiphage defense and allorecognition. These findings add antiphage defense to the functional repertoire of amyloids.
Epigenetic potential and dispersal propensity in a free-living songbird: a spatial and temporal approach
Authors: Jimeno Blanca , Tangili Marianthi , Domínguez Julio C. , Canal David , Camacho Carlos , Potti Jaime , García Jesús T. , Martínez-Padilla Jesús , Ravinet Mark 
Published: November 2024

ABSTRACTNatal dispersal is a key life-history trait determining fitness and driving population dynamics, genetic structure and species distributions. Despite existing evidence that not all phenotypes are equally likely to successfully establish in new areas, the mechanistic underpinnings of natal dispersal remain poorly understood. The propensity to disperse into a new environment can be favored by a high degree of phenotypic plasticity which facilitates local adaptation and may be achieved via epigenetic mechanisms, which modify gene expression and enable rapid phenotypic changes. Epigenetic processes occur in particular genomic regions - DNA methylation on CpG sites in vertebrates -, and thus individual genomes may differ in their capacity to be modified epigenetically. This “Epigenetic potential” (EP) may represent the range of phenotypic plasticity attainable by an individual, and be a key determinant of successful settlement in novel areas. We investigated the association between EP – quantified as the number of genome-wide CpG variants – and natal dispersal propensity in a long-term study population of Pied flycatchers (Ficedula hypoleuca) monitored since colonization of a new habitat 35 years ago. We tested this association at three levels, comparing EP between: i) individuals dispersing between and within habitat patches; ii) immigrants to the population and locally-born individuals; and iii) individuals from first (comprising colonizers or their direct descendants) and later generations of the population (consisting of locally-born individuals, which did not show natal dispersal). Results show a significant, positive association between EP and dispersal propensity in comparisons i) and iii), but not ii). Furthermore, CpG variants were non-randomly distributed across the genome, suggesting species- and/or population-specific CpGs being more frequent in promoters and exons. Our findings point to EP playing a role in dispersal propensity at spatial and temporal scales, supporting the idea that epigenetically-driven phenotypic plasticity facilitates dispersal and environmental coping in free-living birds.