Nat Commun. 2025 May 23;16(1):4786. doi: 10.1038/s41467-025-60064-1.

ABSTRACT

High-throughput massively parallel reporter assays (MPRAs) and phenotype-rich in vivo transgenic mouse assays are two potentially complementary ways to study the impact of noncoding variants associated with psychiatric diseases. Here, we investigate the utility of combining these assays. Specifically, we carry out an MPRA in induced human neurons on over 50,000 sequences derived from fetal neuronal ATAC-seq datasets and enhancers validated in mouse assays. We also test the impact of over 20,000 variants, including synthetic mutations and 167 common variants associated with psychiatric disorders. We find a strong and specific correlation between MPRA and mouse neuronal enhancer activity. Four out of five tested variants with significant MPRA effects affected neuronal enhancer activity in mouse embryos. Mouse assays also reveal pleiotropic variant effects that could not be observed in MPRA. Our work provides a catalog of functional neuronal enhancers and variant effects and highlights the effectiveness of combining MPRAs and mouse transgenic assays.

PMID:40404660 | DOI:10.1038/s41467-025-60064-1

Nat Commun. 2025 May 23;16(1):4785. doi: 10.1038/s41467-025-60154-0.

ABSTRACT

Transcriptomes provide highly informative molecular phenotypes that, combined with gene perturbation, can connect genotype to phenotype. An ultimate goal is to perturb every gene and measure transcriptome changes, however, this is challenging, especially in whole animals. Here, we present 'Worm Perturb-Seq (WPS)', a method that provides high-resolution RNA-sequencing profiles for hundreds of replicate perturbations at a time in living animals. WPS introduces multiple experimental advances combining strengths of Caenhorhabditis elegans genetics and multiplexed RNA-sequencing with a novel analytical framework, EmpirDE. EmpirDE leverages the unique power of large transcriptomic datasets and improves statistical rigor by using gene-specific empirical null distributions to identify DEGs. We apply WPS to 103 nuclear hormone receptors (NHRs) and find a striking 'pairwise modularity' in which pairs of NHRs regulate shared target genes. We envision the advances of WPS to be useful not only for C. elegans, but broadly for other models, including human cells.

PMID:40404656 | DOI:10.1038/s41467-025-60154-0

Nat Commun. 2025 May 22;16(1):4771. doi: 10.1038/s41467-025-59779-y.

ABSTRACT

Kinases regulate cellular processes and are essential for understanding cellular function and disease. To investigate the regulatory state of a kinase, numerous methods have been developed to infer kinase activities from phosphoproteomics data using kinase-substrate libraries. However, few phosphorylation sites can be attributed to an upstream kinase in these libraries, limiting the scope of kinase activity inference. Moreover, inferred activities vary across methods, necessitating evaluation for accurate interpretation. Here, we present benchmarKIN, an R package enabling comprehensive evaluation of kinase activity inference methods. Alongside classical perturbation experiments, benchmarKIN introduces a tumor-based benchmarking approach utilizing multi-omics data to identify highly active or inactive kinases. We used benchmarKIN to evaluate kinase-substrate libraries, inference algorithms and the potential of adding predicted kinase-substrate interactions to overcome the coverage limitations. Our evaluation shows most computational methods perform similarly, but the choice of library impacts the inferred activities with a combination of manually curated libraries demonstrating superior performance in recapitulating kinase activities. Additionally, in the tumor-based evaluation, adding predicted targets from NetworKIN further boosts the performance. We then demonstrate how kinase activity inference aids characterize kinase inhibitor responses in cell lines. Overall, benchmarKIN helps researchers to select reliable methods for identifying deregulated kinases.

PMID:40404650 | DOI:10.1038/s41467-025-59779-y

Sci Data. 2025 May 22;12(1):842. doi: 10.1038/s41597-025-05114-5.

ABSTRACT

The endangered mountain gorilla, Gorilla beringei beringei, faces numerous threats to its survival, highlighting the urgent need for genomic resources to aid conservation efforts. Here, we present a near telomere-to-telomere, haplotype-phased reference genome assembly for a male mountain gorilla generated using PacBio HiFi (26.77× ave. coverage) and Oxford Nanopore Technologies (52.87× ave. coverage) data. The resulting non-scaffolded assembly exhibits exceptional contiguity, with contig N50 of ~95 Mbp for the combined pseudohaplotype (3,540,458,497 bp), 56.5 Mbp (3.1 Gbp) and 51.0 Mbp (3.2 Gbp) for each haplotype, an average QV of 65.15 (error rate = 3.1 × 10-7), and a BUSCO score of 98.4%. These represent substantial improvements over most other available primate genomes. This first high-quality reference genome of the mountain gorilla provides an invaluable resource for future studies on gorilla evolution, adaptation, and conservation, ultimately contributing to the long-term survival of this iconic species.

PMID:40404646 | DOI:10.1038/s41597-025-05114-5

Nat Commun. 2025 May 22;16(1):4759. doi: 10.1038/s41467-025-59839-3.

ABSTRACT

In spatial'omics, highly confident molecular identifications are indispensable for the investigation of complex biology and for spatial biomarker discovery. However, current mass spectrometry imaging (MSI)-based spatial 'omics must compromise between data acquisition speed and biochemical profiling depth. Here, we introduce fast, label-free quantum cascade laser mid-infrared imaging microscopy (QCL-MIR imaging) to guide MSI to high-interest tissue regions as small as kidney glomeruli, cultured multicellular spheroid cores or single motor neurons. Focusing on smaller tissue areas enables extensive spatial lipid identifications by on-tissue tandem-MS employing imaging parallel reaction monitoring-Parallel Accumulation-Serial Fragmentation (iprm-PASEF). QCL-MIR imaging-guided MSI allowed for unequivocal on-tissue elucidation of 157 sulfatides selectively accumulating in kidneys of arylsulfatase A-deficient mice used as ground truth concept and provided chemical rationales for improvements to ion mobility prediction algorithms. Using this workflow, we characterized sclerotic spinal cord lesions in mice with experimental autoimmune encephalomyelitis (EAE), a model of multiple sclerosis, and identified upregulation of inflammation-related ceramide-1-phosphate and ceramide phosphatidylethanolamine as markers of white matter lipid remodeling. Taken together, widely applicable and fast QCL-MIR imaging-based guidance of MSI ensures that more time is available for exploration and validation of new biology by default on-tissue tandem-MS analysis.

PMID:40404613 | DOI:10.1038/s41467-025-59839-3

Food Chem. 2025 May 21:144629. doi: 10.1016/j.foodchem.2025.144629. Online ahead of print.

NO ABSTRACT

PMID:40404507 | DOI:10.1016/j.foodchem.2025.144629

Eur Respir J. 2025 May 22;65(5):2500092. doi: 10.1183/13993003.00092-2025. Print 2025 May.

NO ABSTRACT

PMID:40404195 | DOI:10.1183/13993003.00092-2025

New Phytol. 2025 May 22. doi: 10.1111/nph.70182. Online ahead of print.

ABSTRACT

Evolutionarily conserved switch-defective/sucrose nonfermentable (SWI/SNF) ATP-dependent chromatin remodelling complexes (CRCs) alter nucleosome positioning and chromatin states, affecting gene expression to regulate important processes such as proper development and hormonal signalling pathways. We employed transcript profiling, chromatin immunoprecipitation (ChIP), mass spectrometry, yeast two-hybrid and bimolecular fluorescence complementation protein-protein interaction studies, along with hormone and metabolite profiling and phenotype assessments, to distinguish the SWP73A and SWP73B subunit functions in Arabidopsis. We identified a novel subclass of SWI/SNF CRCs defined by the presence of the SWP73A subunit. Therefore, we propose a refined classification of SWI/SNF CRCs in Arabidopsis, introducing BRM-associated SWI/SNF (BAS)-A (containing SWP73A) and BAS-B (containing SWP73B) subclasses. The SWP73A- and SWP73B-carrying SWI/SNF CRCs exhibit differential properties, demonstrated by distinct chromatin binding patterns and divergent effects on hormone biosynthesis and metabolism. We additionally found that SWP73A plays a specific role in the regulation of auxin signalling, root development, metabolism and germination that cannot be fully compensated by SWP73B. We recognised that some atypical subclasses of SWI/SNF CRCs may be likely formed in mutant lines with inactivated SWP73 subunits. Our study reveals that the duplication of the SWP73 subunit genes contributes to unique and shared functions of SWI/SNF CRC subclasses in the regulation of various processes in Arabidopsis.

PMID:40404167 | DOI:10.1111/nph.70182

Cell Genom. 2025 May 19:100879. doi: 10.1016/j.xgen.2025.100879. Online ahead of print.

ABSTRACT

Identifying cell-type-specific enhancers is critical for developing genetic tools to study the mammalian brain. We organized the "Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics" to evaluate machine learning and feature-based methods for nominating enhancer sequences targeting mouse cortical cell types. Methods were assessed using in vivo data from hundreds of adeno-associated virus (AAV)-packaged, retro-orbitally delivered enhancers. Open chromatin was the strongest predictor of functional enhancers, while sequence models improved prediction of non-functional enhancers and identified cell-type-specific transcription factor codes to inform in silico enhancer design. This challenge establishes a benchmark for enhancer prioritization and highlights computational and molecular features critical for identifying functional cortical enhancers, advancing efforts to map and manipulate gene regulation in the mammalian cortex.

PMID:40403730 | DOI:10.1016/j.xgen.2025.100879

Mol Cell. 2025 May 14:S1097-2765(25)00405-8. doi: 10.1016/j.molcel.2025.04.026. Online ahead of print.

ABSTRACT

Diffuse midline glioma (DMG) is a fatal childhood brain tumor characterized primarily by mutant histone H3 (H3K27M). H3K27M causes a global reduction in Polycomb repressive complex 2 (PRC2)-mediated H3K27 trimethylation (H3K27me3). Paradoxically, PRC2 is essential in DMG cells, although the downstream molecular mechanisms are poorly understood. Here, we have discovered a specific form of canonical PRC1 (cPRC1) containing CBX4 and PCGF4 that drives oncogenic gene repression downstream of H3K27me3 in DMG cells. Via a novel functional region, CBX4 preferentially associates with PCGF4-containing cPRC1. The characteristic H3K27me3 landscape in DMG rewires the distribution of cPRC1 complexes, with CBX4/PCGF4-cPRC1 accumulating at H3K27me3-enriched CpG islands. Despite comprising <5% of cPRC1 in DMG cells, the unique repressive functions of CBX4/PCGF4-cPRC1 are essential for DMG growth. Our findings link the altered distribution of H3K27me3 to imbalanced cPRC1 function, which drives oncogenic gene repression in DMG, highlighting potential therapeutic opportunities for this incurable childhood brain cancer.

PMID:40403727 | DOI:10.1016/j.molcel.2025.04.026

Neuron. 2025 May 21;113(10):1525-1547.e15. doi: 10.1016/j.neuron.2025.05.002.

ABSTRACT

In recent years, we and others have identified a number of enhancers that, when incorporated into rAAV vectors, can restrict the transgene expression to particular neuronal populations. Yet, viral tools to access and manipulate specific neuronal subtypes are still limited. Here, we performed systematic analysis of single-cell genomic data to identify enhancer candidates for each of the telencephalic interneuron subtypes. We established a set of enhancer-AAV tools that are highly specific for distinct cortical interneuron populations and striatal cholinergic interneurons. These enhancers, when used in the context of different effectors, can target (fluorescent proteins), observe activity (GCaMP), and manipulate (opto-genetics) specific neuronal subtypes. We also validated our enhancer-AAV tools across species. Thus, we provide the field with a powerful set of tools to study neural circuits and functions and to develop precise and targeted therapy.

PMID:40403705 | DOI:10.1016/j.neuron.2025.05.002

Plant Physiol Biochem. 2025 May 17;225:110043. doi: 10.1016/j.plaphy.2025.110043. Online ahead of print.

ABSTRACT

A growing number of weed biotypes showing resistance to acetolactate synthase (ALS)-inhibitors have been reported in several species, notably including Sinapis arvensis L. Two putative resistant (R) populations of S. arvensis from Tunisia were subjected to greenhouse and laboratory investigations to validate resistance to ALS-inhibitors and to determinate the mechanisms involved. The results indicated that both populations were resistant to four distinct ALS-inhibiting herbicides, tribenuron-methyl (TM), florasulam, flucarbazone and imazamox (IMZ), thereby confirming cross-resistance between them. The dose of (TM) required to achieve a 50 % reduction in plant growth (ED50) and 50 % mortality (LC50) in R populations of S. arvensis was found to be at least 60 times greater than the recommended field dose (18.7 g ai ha-1) applied in cereal crops in Tunisia, indicating a significantly elevated resistance factor. Synergist experiments using malathion as a cytochrome P450 (Cyt-P450) inhibitor demonstrated a reduction in resistance to imazamox (IMZ) in both resistant (R) biotypes, indicating that Cyt-P450 plays a partial role in the resistance mechanism. In addition, ALS gene analysis identified three key point mutations, Pro197Ala, Asp376Glu and Trp574Leu, in both R populations. The docking analysis demonstrated that Asp376Glu mutation in S. arvensis could confer cross-resistance to IMZ and TM herbicides. CAPS and dCAPS methods were developed for detecting the Trp574Leu and Asp376Glu mutations, respectively, in S arvensis and it was shown that work efficiently. Fortunately, the study also confirmed that 2,4-D still effectively controlled S. arvensis populations. This study provides valuable insights into the mechanisms underlying herbicide resistance in S.arvensis populations from Tunisia, demonstrating that both target-site resistance (TSR) and non-target-site resistance (NTSR) contribute to the species' broad-spectrum resistance against four dissimilar ALS-inhibitors.

PMID:40403623 | DOI:10.1016/j.plaphy.2025.110043

Biomaterials. 2025 May 19;323:123422. doi: 10.1016/j.biomaterials.2025.123422. Online ahead of print.

ABSTRACT

Spinal cord injury (SCI) remains a formidable clinical challenge with limited therapeutic options. Recent advances in nanotechnology have introduced paradigm-shifting strategies that transcend the limitations of traditional treatments by offering precision, controllability, and multifunctionality in modulating the hostile post-injury microenvironment. This review systematically summarizes nanotechnology-based therapeutic approaches for SCI, including cell-based nanotherapeutics, nanogels/hydrogels, nano-engineered materials, and combinatorial strategies. We emphasize the synergistic design of multifunctional nanoplatforms that integrate neuroprotection, immune modulation, antioxidative capacity, and axonal regeneration within a single system. Special attention is given to microenvironment-responsive smart materials capable of dynamic therapeutic delivery in response to pathological cues. We critically analyze the challenges of clinical translation, such as the need for standardized safety evaluation and personalized therapeutic dosing, and explore emerging solutions including AI-driven nanocarrier design and organoid-based validation. By integrating interdisciplinary innovations, nanotherapies represent an irreplaceable therapeutic paradigm with the potential to achieve spatiotemporal precision and sustained regenerative support for SCI repair.

PMID:40403446 | DOI:10.1016/j.biomaterials.2025.123422

Stat Med. 2025 May;44(10-12):e70059. doi: 10.1002/sim.70059.

ABSTRACT

Intra-patient dose escalation (IPDE) provides a strategy for more efficient Phase I clinical trials. However, IPDE poses additional challenges due to the need to account for carryover toxicity from previous dosings a patient has received. To that end, we propose two CRM-based approaches to IPDE that incorporate potential carryover toxicity. We compare these methods to the CRM without IPDE and the AIDE-CRM, an existing Bayesian adaptive approach to IPDE. In simulations across a range of scenarios, we show that our approaches have similar operating characteristics to the CRM without IPDE, but with a 20% reduction in time and participants needed to complete the trial; these results hold even in the presence of strong carryover toxicity that hinders the performance of the AIDE-CRM.

PMID:40405047 | DOI:10.1002/sim.70059

Database (Oxford). 2025 May 20;2025:baaf008. doi: 10.1093/database/baaf008.

ABSTRACT

We previously described Graph2VR, a prototype that enables researchers to use virtual reality (VR) to explore and navigate through Linked Data graphs using SPARQL queries (see https://doi.org/10.1093/database/baae008). Here we evaluate the use of Graph2VR in three realistic life science use cases. The first use case visualizes metadata from large-scale multi-center cohort studies across Europe and Canada via the EUCAN Connect catalogue. The second use case involves a set of genomic data from synthetic rare disease patients, which was processed through the Variant Interpretation Pipeline and then converted into Resource Description Format for visualization. The third use case involves enriching a graph with additional information, in this case, the Dutch Anatomical Therapeutic Chemical code Ontology with the DrugID from Drugbank. These examples collectively showcase Graph2VR's potential for data exploration and enrichment, as well as some of its limitations. We conclude that the endless three-dimensional space provided by VR indeed shows much potential for the navigation of very large knowledge graphs, and we provide recommendations for data preparation and VR tooling moving forward. Database URL: https://doi.org/10.1093/database/baaf008.

PMID:40402773 | DOI:10.1093/database/baaf008

Sante Publique. 2025;37(1):209-223. doi: 10.3917/spub.251.0209.

ABSTRACT

INTRODUCTION: The care paths and lives of cystic fibrosis patients were profoundly altered during the health crisis in France. Patient experiences can be used to provide lessons on how to adapt to a crisis.

PURPOSE OF THE STUDY: The ExPaParM collaborative study analyzed the experiences of a varied sample of patients and identified changes in practices in Cystic Fibrosis Centers (CFC), with the aim of characterizing adaptations made and destabilizing events experienced during this crisis, using a systemic approach.

RESULTS: Adaptation practices aiming to minimize the impact of the crisis or maintain the recommended quality of care, as far as possible, have been identified. These adaptations concern the individual level (patient and family), local care, care management at CFCs, and hospital organization. When the crisis has negatively affected patients, resilience factors based on individual and family skills, a relationship of trust with professionals, and informal solidarity networks have enabled complex situations to be overcome.

CONCLUSION: Strong points prior to the crisis proved decisive: the structuring of CFC teams, digital resources, therapeutic patient education, and a circuit for disseminating information related to cystic fibrosis. Reducing vulnerability to a future crisis also means securing essential medicines for the disease, organizing protected hospital circuits, and developing patient preparedness plans.

PMID:40402727 | DOI:10.3917/spub.251.0209

Acta Microbiol Immunol Hung. 2025 May 22. doi: 10.1556/030.2025.02578. Online ahead of print.

ABSTRACT

Stenotrophomonas maltophilia has emerged as an opportunistic pathogen originating from the environments, causing nosocomial infections, particularly in immunocompromised individuals and patients with cystic fibrosis. Although this microorganism exhibits low virulence, its infections are associated with high morbidity and mortality rates. S. maltophilia is intrinsically resistant to many antimicrobial agents used in clinical practices, therefore, posing significant treatment challenges. The multidrug resistance in S. maltophilia results from a combination of intrinsic, adaptive, and acquired mechanisms. S. maltophilia genome carries an array of genes encoding multidrug efflux pumps, which are key contributors to its broad-spectrum antibiotic resistance by expelling a wide range of drugs and reducing their intracellular concentrations to nontoxic levels. The majority of these efflux pumps belong to the resistance-nodulation-cell division (RND) family, while a lesser fraction is classified under the major facilitator superfamily (MFS) and the adenosine triphosphate binding cassette (ABC) family. In terms of function, substrate specificity, and complex gene regulation, these multidrug efflux pumps contribute not only to the survival of S. maltophilia under antibiotic stress but also to its resilience against other chemical challenges, including oxidative stress-generating substances and biocides. The roles of certain efflux pump systems in acquired and adaptive antibiotic resistance, as well as their potential applications as drug targets to enhance the efficacy of routinely used antibiotics through the use of small molecules capable of functioning as efflux pump inhibitors, are also discussed. A deeper understanding of these mechanisms can contribute to the more effective management against antibiotic-resistant S. maltophilia.

PMID:40402604 | DOI:10.1556/030.2025.02578

Clin Radiol. 2025 Apr 24;86:106941. doi: 10.1016/j.crad.2025.106941. Online ahead of print.

ABSTRACT

AIM: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has proven to be highly sensitive in diagnosing breast tumours, due to the kinetic and volumetric features inherent in it. To utilise the kinetics-related and volume-related information, this paper aims to develop and validate a classification for differentiating benign and malignant breast tumours based on DCE-MRI, though fusing deep features and cross-attention-encoded radiomics features using discriminant correlation analysis (DCA).

MATERIALS AND METHODS: Classification experiments were conducted on a dataset comprising 261 individuals who underwent DCE-MRI including those with multiple tumours, resulting in 137 benign and 163 malignant tumours. To improve the strength of correlation between features and reduce features' redundancy, a novel fusion method that fuses deep features and encoded radiomics features based on DCA (eFF-DCA) is proposed. The eFF-DCA includes three components: (1) a feature extraction module to capture kinetic information across phases, (2) a radiomics feature encoding module employing a cross-attention mechanism to enhance inter-phase feature correlation, and (3) a DCA-based fusion module that transforms features to maximise intra-class correlation while minimising inter-class redundancy, facilitating effective classification.

RESULTS: The proposed eFF-DCA method achieved an accuracy of 90.9% and an area under the receiver operating characteristic curve of 0.942, outperforming methods using single-modal features.

CONCLUSION: The proposed eFF-DCA utilises DCE-MRI kinetic-related and volume-related features to improve breast tumour diagnosis accuracy, but non-end-to-end design limits multimodal fusion. Future research should explore unified end-to-end deep learning architectures that enable seamless multimodal feature fusion and joint optimisation of feature extraction and classification.

PMID:40403340 | DOI:10.1016/j.crad.2025.106941

PLoS One. 2025 May 22;20(5):e0323757. doi: 10.1371/journal.pone.0323757. eCollection 2025.

ABSTRACT

Salient Object Detection (SOD) is a fundamental task in computer vision, aiming to identify prominent regions within images. Traditional methods and deep learning-based models often encounter challenges in capturing crucial information in complex scenes, particularly due to inadequate edge feature extraction, which compromises the precise delineation of object contours and boundaries. To address these challenges, we introduce EFCRFNet, a novel multi-scale feature extraction model that incorporates two innovative modules: the Enhanced Conditional Random Field (ECRF) and the Edge Feature Enhancement Module (EFEM). The ECRF module leverages advanced spatial attention mechanisms to enhance multimodal feature fusion, enabling robust detection in complex environments. Concurrently, the EFEM module focuses on refining edge features to strengthen multi-scale feature representation, significantly improving boundary recognition accuracy. Extensive experiments on standard benchmark datasets demonstrate that EFCRFNet achieves notable performance gains across key evaluation metrics, including MAE (0.64%), Fm (1.04%), Em (8.73%), and Sm (7.4%). These results underscore the effectiveness of EFCRFNet in enhancing detection accuracy and optimizing feature fusion, advancing the state of the art in salient object detection.

PMID:40403088 | DOI:10.1371/journal.pone.0323757

Science. 2025 May 22;388(6749):eadr7094. doi: 10.1126/science.adr7094. Epub 2025 May 22.

ABSTRACT

Deep learning has advanced the design of static protein structures, but the controlled conformational changes that are hallmarks of natural signaling proteins have remained inaccessible to de novo design. Here, we describe a general deep learning-guided approach for de novo design of dynamic changes between intradomain geometries of proteins, similar to switch mechanisms prevalent in nature, with atomic-level precision. We solve four structures that validate the designed conformations, demonstrate modulation of the conformational landscape by orthosteric ligands and allosteric mutations, and show that physics-based simulations are in agreement with deep-learning predictions and experimental data. Our approach demonstrates that new modes of motion can now be realized through de novo design and provides a framework for constructing biology-inspired, tunable, and controllable protein signaling behavior de novo.

PMID:40403060 | DOI:10.1126/science.adr7094