bluuebunny/crossref_metadata_2025_split huggingface dataset:
DMRU: Generative Deep-Learning to unravel condition specific cytosine methylation in plants
Authors: Gupta Sagar , Kumar Anchit , Kesarwani Veerbhan , Shankar Ravi 
Published: February 2025

AbstractEpigenetic regulation of gene expression is a complex and multifaceted process that plays a crucial role in plant development and adaptation. DNA methylation at cytosines has been shown to influence gene expression by regulating chromatin structure and accessibility. Some approaches have been developed to identify DNA methylation but none of them are capable to tell the condition specific DNA methylation, making them hardly of any use. Here, we report a first of its kind an explainable Deep Encoders-Decoders generative system, DMRU, which learns the relationship between transcritpome status and DNA methylation states at any given time. It was also found that instead of looking for homology to relate condition specificity of DNA methylation marks across species, GC similarity is more relevant to the specificity of DNA methylation patterns. The developed approach, DMRU, is capable to discover the methylated cytosines in total independence from data volume and species specific models, and works with same performance across different species in universal manner. In a comprehensive benchmarking study across a huge volume of experimental data covering different conditions and species, it has consistently achieved >90% accuracy. With this all, DMRU brings a completely new chapter in methylated cytosine discovery through generative AI, giving a strong alternative to costly bisulfite sequencing experiments, saving enormous amount of time and money. DMRU may have significant impact on the development of novel strategies for crop improvement and biotechnology applications, while accelerating the research in the field of epigenomics and gene regulation. DMRU is freely available as a web-server athttps://scbb.ihbt.res.in/DMRU/index.php.
Water parameters and hydrodynamics in rivers and caves hostingAstyanax mexicanuspopulations reveal macro-, meso- and micro-habitat characteristics
Authors: Legendre Laurent , Père Stéphane , Rebaudo François , Espinasa Luis , Rétaux Sylvie 
Published: February 2025

AbstractThe Mexican tetra (Astyanax mexicanus) has emerged as a leading model for evolutionary biology and the study of adaptation to extreme subterranean environments. The river-dwelling morphs of the species are distributed in Mexico and Texas, while the blind and cave-adapted morphs inhabit the karstic caves of the Sierra Madre Oriental in northeastern Mexico. Although the molecular, cellular and genetic underpinnings ofAstyanaxcavefish evolution are being elucidated, our understanding of its habitat and environment remains limited, thereby constraining the interpretations of its morphological, physiological, and behavioral adaptations. In particular, the physico-chemical parameters of the water and the hydrological regimes to which cavefish are subjected remain largely unexplored. From 2009 to 2024, we have recorded the physico-chemical parameters of the water in whichAstyanax mexicanuscavefish and surface fish are found in the El Abra and La Colmena regions of the states of San Luis Potosí and Tamaulipas, Mexico. Data were collected using a variety of devices and probes, including both point and longitudinal measurements of water quality. A total of 13 caves out of the 33 knownAstyanaxcaves and 27 surface stations (rivers, springs, ponds) were sampled. The comparison of epigean and hypogean waters showed strong signatures of the two macro-habitats. As compared to surface, cave water was fresher, much less conductive and highly anoxic. Moreover, at the meso-habitat level, a comparison between caves revealed significant differences in both specific water parameters and hydrological regimes. One- or two-year longitudinal recordings demonstrated that some caves exhibited relatively stable hydrological regimes, while others experienced multiple, sudden and significant fluctuations. Finally, distinct pools within a single cave showed notable differences, displaying a highly reproducible increase in water temperature as a function of depth or distance from the cave entrance, and revealing specificities at the micro-habitat level. Our comprehensive dataset on cave water quality and hydrodynamics is interpreted in the context of an integrated view of cave biology and the evolution of cave organisms. Our findings have significant implications for understanding the evolution of cavefishes and the biology of the species in general.
Sensory neurons shape macrophage identity via TGF-β signalling
Authors: Kolter Julia , Döring Clarissa-Laura , Baasch Sebastian , Alsumati Reem , Mansoori Moghadam Zohreh , Gres Vitka , Lohrmann Florens , da Silva Gabriel Victor Lucena , Silva Conceicao Elidianne Anibal , Buchegger Theresa , Doumard Layal , Voisin Benjamin , Lachmann Nico , Kierdorf Katrin , Flacher Vincent , Henneke Philipp 
Published: February 2025

SUMMARYMacrophages play integral roles in maintaining homeostasis and function in their tissues of residence. In the skin, prenatally seeded and highly specialized macrophages physically interact with sensory nerves and contribute to their regeneration after injury. However, mechanisms underlying the development and maintenance of this potentially lifelong commitment of macrophages to nociceptors remain largely elusive. Here, we found that infiltrating myeloid progenitor cells approached the sprouting axons of sensory nerves and gradually adopted a nerve-associated macrophage-like profile. This change in identity was steered and maintained by the immediate microenvironment, in particular TGF-β, which was locally activated by the physical interaction with nerves and integrin-mediated cleavage. Following injury, TGF-β driven specification of macrophages essentially supported nerve regeneration. Overall, we identified TGF-β as a central mediator governing local imprinting and long-term specialization of macrophages in the skin, providing insights into the bidirectional communication between macrophages and sensory nerves.
Organisation of axial regions of isolated mitotic chromosomes visualised by cryo correlative light and electron tomography
Authors: Patra Gurudatt , Harastani Mohamad , Samejima Kumiko , Remnant Lucy , Troffer-Charlier Nathalie , Crucifix Corrine , Durand Alexandre , Marechal Nils , Lutz Yves , Steyer Anna M. , Yang Zhengyi , Hagen Wim J. H. , Earnshaw William C. , Eltsov Mikhail 
Published: February 2025

AbstractThe formation of mitotic chromosomes is essential for the accurate segregation of genetic material during cell division. Increasing evidence suggests that chromosome formation involves the reorganization of DNA into loops anchored within chromosomal axial regions, whose structural organization remains insufficiently characterized. Taking advantage of DT40 cells, an avian cell model characterized by the presence of a range of chromosome sizes from 3.2-197 Mb, we have established a preparation of entire close-to-native native mitotic chromosomes for cryogenic correlative light and electron microscopy (cryo-CLEM). The size of the smallest chromosomes allows imaging of their axial regions without further thinning. Cryo-electron tomography of the chromosome axial regions reveals the presence of heterogeneous non-histone macromolecular densities (NHMDs), approximately 30–45 nm in size, interspersed within chromatin/DNA regions. We propose that NHMDs may contain condensins and contribute to chromosome architecture. In addition to NHMDs, we identified dense clusters of particles, similar in size, near the chromosome surface, likely associated with ribosomal components. To quantitatively differentiate NHMDs from these surface clusters, we developed an analytical approach based on particle interspacing and spatial distribution within the chromosome volume. By establishing a cryo-CLEM workflow for whole, near-native mitotic chromosomes, our study provides a foundation for investigating their ultrastructural architecture.
The strength of the fecundity-immunity trade-off modulates host evolutionary dynamics, pathogen propagation, and host abundance
Authors: Djahoui Edgard , Loeuille Nicolas , Rohr Rudolf P. 
Published: February 2025

AbstractIn most species, life history trade-offs generate conflicts between several biological functions because of resource allocation constraints. If under a pathogenic infection, the host can trigger some defense mechanisms against the pathogen, there is usually a fitness cost associated in terms of fecundity reduction. This pattern, known as the fecundity-immunity trade-off, has received much attention, but its implications on host eco-evolutionary dynamics, and particularly on emergent properties such as host abundance and pathogen propagation remain poorly understood. Here, we use an SIR model that incorporates three distinct host immune mechanisms, which are a reduction in pathogen transmission, an increase in host recovery, and a reduction in pathogen-associated host death. Our results indicate that the effect of a fecundity-immunity trade-off depends not only on its strength, but also on the particular immune mechanism considered. We found that, in all three immune mechanisms, for a weak trade-off, the host evolves simultaneously toward high fecundity and high immunity, while for a strong trade-off, high fecundity is selected at the expense of immunity. Intermediate trade-off results in two distinct alternative evolutionary strategies; high fecundity and low immunity, and low fecundity and high immunity. Moreover, we show that disease propagation and host abundance usually show opposite dynamics along the evolutionary trajectories. We here believe that the incorporation of this trade-off in further analysis of host-pathogen interactions may help to better understand the complexity of the ecological and evolutionary dynamics in such systems.
N-Power AI: A Specialized Agent Framework for Automated Sample Size and Power Analysis in Clinical Trial Design
Authors: Ruan Peifeng , Villanueva-Miranda Ismael , Liu Jialiang , Yang Donghan M. , Zhou Qinbo , Xiao Guanghua , Xie Yang 
Published: February 2025

AbstractBackgroundSample size and power analysis are essential in biomedical research and investigations, particularly in clinical trial design, as they ensure sufficient statistical power to detect meaningful effects. However, the complexity of these calculations often requires specialized statistical expertise, making the process inconvenient and limiting accessibility for researchers during early-stage study planning.MethodsWe developed N-Power AI, an agentic framework leveraging large language models (LLMs) to perform sample size and power calculations across diverse study designs. The framework consists of three specialized agents: the Function Agent, a perception and reasoning module that identifies appropriate statistical tests and corresponding R functions; the Calculation Agent, an action module that extracts parameters and executes precise computations; and the Reporting Agent, a presentation module that generates comprehensive, downloadable reports. N-Power AI and advanced LLMs (e.g., GPT-o1, Claude 3.5, Gemini 1.5 Pro) were evaluated against ground truths from statistical software (R) across six common clinical trial scenarios.ResultsDirect LLM outputs showed significant deviations from ground-truth values, particularly in complex scenarios like the Chi-Square Test and Cox Proportional Hazards Model. In contrast, N-Power AI achieved 100% agreement with ground truths across all scenarios. This accuracy is attributed to the Function Agent’s correct selection of statistical methods, the Calculation Agent’s accurate computations, and the Reporting Agent’s ability to produce clear and comprehensive summaries.ConclusionN-Power AI automates sample size and power analysis, offering an effective, efficient, and accessible solution for early-stage study planning. While human expertise remains crucial for high-level statistical planning, N-Power AI enhances accessibility and efficiency, streamlining the analysis process to generate reliable and reproducible results for a wide range of research scenarios.
Microtubule remodeling by the innate immune factor Trim69 compromises dynein-dependent migration of HIV virion cores towards the nucleus
Authors: Vadon Charlotte , Nguyen Xuan-Nhi , Siahaan Valerie , Krishnan Arya , Henriot Veronique , Chantharath Amandine , Burlaud-Gaillard Julien , Roingeard Philippe , Janke Carsten , Etienne Lucie , Fiorini Francesca , Magiera Maria M. , Cimarelli Andrea 
Published: February 2025

AbstractLike many viruses, HIV relies on the microtubule (MT) cytoskeleton for successful infection. MT-associated proteins (MAPs) regulate MT functions and thus bear the potential to modulate viral infection. However, while several MAPs are known to exert pro-viral effects on HIV, little is known about antiviral ones. We previously described the Tripartite motif protein 69 (Trim69) as an innate immune factor that remodels MTs, leading to inhibition of a broad spectrum of viruses, including HIV. Through in silico modeling, TIRF microscopy and cell-based assays, we determine that Trim69 binding to MTs is determined by a basic surface in its SPRY domain that interacts with the C-terminal tails of tubulins. This surface is conserved among mammalian Trim69s and is critical for its functions. We demonstrate that by binding and remodeling MTs, Trim69 inhibits the docking and the migration of virion cores on MTs by promoting the stalling of the dynein/dynactin motor complexes. Altogether, these findings shed light on a novel mechanism of viral defense that involves an innate immune regulation of the MT cytoskeleton.
LimROTS: A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Differential Expression Analysis
Authors: Anwar Ali Mostafa , Jeba Akewak , Lahti Leo , Coffey Eleanor 
Published: February 2025

AbstractMotivationDifferential expression analysis plays a vital role in omics research enabling precise identification of features that associate with different phenotypes. This process is critical for uncovering biological differences between conditions, such as disease versus healthy states. In proteomics, several statistical methods have been used, ranging from simple t-tests to more advanced methods like limma and ROTS. However, a flexible method for reproducibility-optimized statistics tailored for clinical omics data has been lacking.ResultsIn this study, we developed LimROTS, a hybrid method integrating the linear model and empirical Bayes method from the limma framework with the Reproducibility-Optimized Statistics from ROTS, to create a novel moderated ranking statistic, for robust and flexible analysis of proteomics data. We validated its performance using twenty-one proteomics gold standard spike-in datasets with different protein mixtures, MS instruments, and techniques for benchmarking. This hybrid approach improves accuracy and reproducibility of complex proteomics data, making LimROTS a powerful tool for high-dimensional omics data analysis.Availability and ImplementationLimROTS has been implemented as an R/Bioconductor package, available athttps://bioconductor.org/packages/LimROTS/. Additionally, the code used in this study is available in GitHub repositoryhttps://github.com/AliYoussef96/LimROTSmanuscriptGraphical abstract
Convergent evolution of distinct D-ribulose utilisation pathways in attaching and effacing pathogens
Authors: Cottam Curtis , Bowran Kieran , White Rhys T. , Baslé Arnaud , Josts Inokentijs , Connolly James PR 
Published: February 2025

AbstractAttaching and effacing pathogens overcome colonisation resistance by competing with metabolically similar organisms for limited resources. EnterohaemorrhagicE. coli(EHEC) utilises the pathogenicity island-encoded Accessory ʟ-arabinose Uptake (Aau) transporter to effectively colonise the mouse gut, hypothesised to be achieved via an enhanced capacity to scavenge ʟ-arabinose. Aau is regulated exclusively in response to ʟ-arabinose, but it is unclear how this system specifically benefits EHECin vivo. Here, we show that Aau displays a >200-fold higher affinity for the monosaccharide D-ribulose, over ʟ-arabinose. EHEC cannot grow on D-ribulose as a sole carbon source and this sugar does not triggeraautranscription. However, Aau effectively transports D-ribulose into the cell only in the presence of ʟ-arabinose, where it feeds into the pentose phosphate pathway, after phosphorylation by the ʟ-ribulokinase AraB, thus providing EHEC a significant fitness advantage. EHEC has therefore evolved a mechanism of hijacking the canonical ʟ-arabinose utilisation machinery to promote D-ribulose utilisationin vivo. Furthermore,Citrobacter rodentiumencodes an analogous system that exclusively transports D-ribulose and metabolises it via a dedicated D-ribulokinase. These unique mechanisms of D-ribulose utilisation suggest that convergent evolution has driven the ability of distinct pathogenic species to exploit this nutrient during invasion of the gut niche.
RNAprecis: Prediction of full-detail RNA conformation from the experimentally best-observed sparse parameters
Authors: Wiechers Henrik , Williams Christopher J. , Eltzner Benjamin , Hoppe Franziska , Prisant Michael G. , Chen Vincent B. , Miller Ezra , Mardia Kanti V. , Richardson Jane S. , Huckemann Stephan F. 
Published: February 2025

AbstractWe address the problem of predicting high detail RNA structure geometry from the information available in low resolution experimental maps of electron density. Here low resolution refers to ⪆ 2.5Åwhere the location of the phosphate groups and the glyocosidic bonds can be determined from electron density but all other backbone atom positions cannot. In contrast, high resolution determines all backbone atomic positions. To this end, we firstly create a gold standard data base for four groups of manually corrected suites, each reflecting one out of four sugar pucker-pair configurations. Secondly we develop and employ a modified version of the previously devised algorithm MINT-AGE to learn clusters that are in high correspondence with gold standard’s conformational classes based on 3D RNA structure. Since some of the manually corrected classes are of very small size, the modified version of MINT-AGE is able to also identify very small clusters. Thirdly, the new algorithm RNAprecis assigns low resolution structures to newly designed 3D shape coordinates. Our improvements include: (i) learned classes augmented to cover also very low sample sizes and (ii) regularizing a key distance by introducing an adaptive Mahalanobis distance. On a test data containing many clashing and suites modeled as conformational outliers, RNA precis shows good results suggesting that our learning method generalizes well. In particular, our modified MINT-AGE clustering can be finer than the existing curated gold standard suite conformers. For example, the0aconformer has been separated into two clusters seen in different structural contexts. Such new distinctions can have implications for biochemical interpretation of RNA structure.Code availabilitThe code used to generate the analyses and plots presented in this paper can be foundhttps://gitlab.gwdg.de/henrik.wiechers1/rnaprecis
Diversity, structure-function relationships and evolution of cell wall-binding domains of staphylococcal phage endolysins
Authors: Vázquez Roberto , Gutiérrez Diana , Criel Bjorn , Dezutter Zoë , Briers Yves 
Published: February 2025

ABSTRACTEndolysins, encoded by phages, lyse bacterial hosts at the end of the replication cycle by degrading peptidoglycan. Consequently, they have evolved in response to host cell wall structures, leading to complex modular architectures, particularly in Gram-positive bacteria. These architectures feature diverse enzymatically active domains (EADs) and cell wall-binding domains (CBDs).This study investigates the structure-function relationships of CBDs in staphylococcal phage endolysins, exploring their evolutionary origins and the extent to which binding specificity can be predicted from sequence data. A set of 182 staphylococcal endolysin sequences was analyzed, revealing predominantly three-domain architectures, occasionally disrupted by species-specific mobile genetic elements. Most CBDs exhibited an SH3-like fold, classified into two major subfamilies: SH3b_P (including the well-characterized SH3_5 family) and SH3b_T. The composition of endolysin domains correlated with specific CBD families, suggesting co-evolution of CBDs and compatible EADs to ensure functional synergy.To assess binding properties, 24 CBDs were fused to eGFP and tested against a panel of staphylococci, revealing diverse specificity profiles. However, no clear correlation emerged between binding specificity, phylogenetic subgroups, or bacterial hosts. This suggests that minor structural modifications significantly impact function and that CBD specificity is not a major selective pressure in the staphylococcal bacteria-phage interface.
The offensive role of theBacillusextracellular matrix in driving metabolite-mediated dialogue and adaptive strategies with pathogenic fungi
Authors: Pérez-Lorente Alicia I. , Molina-Santiago Carlos , Vela-Corcía David , Stincone Paolo , Hierrezuelo Jesús , Grifé Montserrat , Pakkir Shah Abzer K. , de Vicente Antonio , Petras Daniel , Romero Diego 
Published: February 2025

AbstractBacterial□fungal interactions have traditionally been attributed to secondary metabolites, but the role of the bacterial extracellular matrix (ECM) in shaping these relationships has remained unclear. Here, we demonstrate that the ECM protein TasA is a key mediator in the antagonistic interaction betweenBacillus subtilisandBotrytis cinerea. TasA enablesBacillusto tightly adhere to fungal hyphae, disrupts the β-glucan layer, and compromises fungal cytoskeletal integrity synergistically with fengycin, which causes cytological damage. Additionally, TasA acts as a carrier for bacillaene, amplifying its fungistatic activity. In response,B. cinereamounts a multifaceted defense, enzymatically degrading fengycin, producing antibacterial oxylipins, and activating adaptive programs such as hyphal branching and chlamydospore formation. Our findings reveal the previously unrecognized role of ECM components in fungal suppression and the modulation of fungal adaptive responses. This study reveals the complex interplay between microbial aggression and defense, providing new insights into the ecological dynamics of microbial competition and coexistence.
ggalign: Bridging the Grammar of Graphics and Biological Multilayered Complexity
Authors: Peng Yun , Song Yuxuan , Luo Peng , Li Jianfeng , Zhou Jian-Guo , Yu Guangchuang , Xu Tao , Wang Shixiang 
Published: February 2025

AbstractComposable visualization is essential in biomedical research, particularly when working with complex, multi-dimensional biological data. However, many existing tools focus on specific fields and lack the comprehensive features needed to capture the intricacies and interrelations of datasets. To address this, we introduce ggalign, an R package built on the grammar of graphics framework, providing an easy-to-use platform for creating composable visualizations of interconnected data. It offers a variety of layout options, includingStackLayout, QuadLayout, andCircleLayout, tailored to different data types, and supports flexible multi-dimensional relationships, such as one-to-many, many-to-one, many-to-many, and crosswise connections. Additionally, ggalign enhances the clarity of visualizations through its annotation features. Overall, ggalign offers a powerful and flexible solution for visualizing complex data in biomedical research.Abstract Figure