Curr Biol. 2025 Apr 21;35(8):R298-R300. doi: 10.1016/j.cub.2025.03.021.

ABSTRACT

Duckweeds are among the smallest and fastest-growing flowering plants. In a new study that combines experimental data with phylogenomic comparisons across the clade, the authors explore how changes in gene content, epigenetic pathways, and their interplay shaped the body plan, aquatic lifestyle, and clonal growth habit of this plant family.

PMID:40262538 | DOI:10.1016/j.cub.2025.03.021

Cognition. 2025 Apr 21;261:106144. doi: 10.1016/j.cognition.2025.106144. Online ahead of print.

ABSTRACT

The ability to learn new environments is a foundational human skill, yet we know little about how exploration behaviors shape spatial learning. Here, we investigated the relationships between exploration behaviors and spatial memory in healthy young adults, and further related performance to other measures of individual differences. In the present study, 100 healthy young adults (ages 18-37) freely explored a maze in a virtual desktop environment to learn the locations of 9 objects. Participants then navigated from one object to another without feedback, and their accuracy and path efficiency were determined. Interestingly, participant accuracy ranged from near 0 % to 100 %. Correlations and principal component regression revealed that evenness of exploration (i.e., visiting all locations with a similar frequency) and how quickly all objects were found during exploration were related to performance. Indeed, differences in performance become apparent by the time participants found the 6th object (within the first 50 moves), emphasizing the importance of exploration quality over exploration quantity. Perspective taking ability and video game experience were also related to performance. Critically, we found no correlations between performance on matched pairs of active-passive exploration paths, suggesting that experiencing a "good" exploration path does not lead to better performance; instead, the path is more likely a reflection of the navigator's ability. Sex differences were observed, however, a serial mediation analysis revealed that even exploration had a greater explanatory effect on those sex differences compared to video game experience. Our results indicate that exploration behaviors predict navigational performance and highlight the importance of moment-to-moment behaviors exhibited during exploration and learning.

PMID:40262422 | DOI:10.1016/j.cognition.2025.106144

J Hazard Mater. 2025 Apr 17;493:138330. doi: 10.1016/j.jhazmat.2025.138330. Online ahead of print.

ABSTRACT

Polycarbonate (PC), a widely used thermoplastic, poses significant environmental challenges due to its persistence and the release of bisphenol A (BPA), a known xenoestrogen. Here, we report the isolation of Bacillus subtilis JNU01 (BsJNU01), capable of utilizing PC as its sole carbon source. Through transcriptomic analysis, we identified metallophosphoesterase from BsJNU01 (BsMPPE), the first reported metallophosphoesterase capable of degrading polycarbonate by catalyzing the hydrolysis of carbonate ester bonds. This enzyme operates under mild aqueous conditions (30 °C, pH 7), releasing 30 μmol of BPA as a monomer and demonstrating effective PC degradation under environmentally friendly conditions. PC biodegradation was confirmed by Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance (NMR), and gas chromatography-mass spectrometry (GC-MS). Furthermore, surface and mechanical analyses revealed significant degradation and structural changes in PC films following BsMPPE treatment, with toughness showing a 40-70 % decrease compared to untreated PC films. This study represents a breakthrough in microbial plastic degradation, establishing a sustainable biocatalytic platform for PC recycling and upcycling technologies.

PMID:40262317 | DOI:10.1016/j.jhazmat.2025.138330

Emerg Microbes Infect. 2025 Apr 22:2497302. doi: 10.1080/22221751.2025.2497302. Online ahead of print.

ABSTRACT

ABSTRACTChronic obstructive pulmonary disease (COPD) and aging both increase the risk of tuberculosis (TB), an important infectious disease in human. Exploring the burden and predictors of latent tuberculosis infection (LTBI) and treatment outcomes for older individuals with COPD is essential to guide LTBI intervention policy. We enrolled patients aged over 60 years with COPD between January 2021 and June 2023 for LTBI screening using interferon-gamma release assay (IGRA). LTBI treatment options included all WHO-recommended regimens. The final regimen was selected through shared decision-making between patients and their COPD physicians, leveraging the long-standing rapport being established. We investigated the prevalence of LTBI in this population, identified risk factors using logistic regression analysis, and evaluated treatment outcomes. A total of 810 COPD patients (mean: 72.8-years) underwent LTBI screening, with an IGRA-positive rate of 23.8%. IGRA positivity was correlated with smoking pack-years (adjusted odds ratio [aOR]: 1.02, p < 0.001), current smoking status (aOR 1.40, p = 0.030), COPD duration (aOR 1.10, p = 0.03), inhaled corticosteroid use (aOR 3.06, p < 0.001), and a cumulative equivalent dose of prednisolone exceeding 210 mg over 2 years (aOR 3.13, p < 0.001). Treatment was initiated in 150 patients (77.7%), predominantly with weekly rifapentine plus isoniazid (3HP) (60.7%). The overall completion rate was 82.0%, with adverse reactions being the primary reason for discontinuation. Our findings support that the LTBI intervention is recommended for older patients with COPD, especially those at higher risk, as nearly 25% of them have tuberculosis infection. The high treatment completion rate highlights the safety and feasibility of the WHO-recommended regimens.

PMID:40262275 | DOI:10.1080/22221751.2025.2497302

ACS Synth Biol. 2025 Apr 22. doi: 10.1021/acssynbio.4c00868. Online ahead of print.

ABSTRACT

Researchers have invested much effort into developing kinetic models due to their ability to capture dynamic behaviors, transient states, and regulatory mechanisms of metabolism, providing a detailed and realistic representation of cellular processes. Historically, the requirements for detailed parametrization and significant computational resources created barriers to their development and adoption for high-throughput studies. However, recent advancements, including the integration of machine learning with mechanistic metabolic models, the development of novel kinetic parameter databases, and the use of tailor-made parametrization strategies, are reshaping the field of kinetic modeling. In this Review, we discuss these developments and offer future directions, highlighting the potential of these advances to drive progress in systems and synthetic biology, metabolic engineering, and medical research at an unprecedented scale and pace.

PMID:40262025 | DOI:10.1021/acssynbio.4c00868

Plant Cell. 2025 Apr 2;37(4):koaf056. doi: 10.1093/plcell/koaf056.

ABSTRACT

Plants use environmental cues to orient organ and plant growth, such as the direction of gravity or the direction, quantity, and quality of light. During the germination of Arabidopsis thaliana seeds in soil, negative gravitropism responses direct hypocotyl elongation such that the seedling can reach the light for photosynthesis and autotrophic growth. Similarly, hypocotyl elongation in the soil also requires mechanisms to efficiently grow around obstacles such as soil particles. Here, we identify KIPK (KINESIN-LIKE CALMODULIN-BINDING PROTEIN-INTERACTING PROTEIN KINASE) and the paralogous KIPKL1 (KIPK-LIKE1) as genetically redundant regulators of gravitropic hypocotyl bending. Moreover, we demonstrate that the homologous KIPKL2 (KIPK-LIKE2), which shows strong sequence similarity, must be functionally distinct. KIPK and KIPKL1 are polarly localized plasma membrane-associated proteins that can activate PIN-FORMED auxin transporters. KIPK and KIPKL1 are required to efficiently align hypocotyl growth with the gravity vector when seedling hypocotyls are grown on media plates or in soil, where contact with soil particles and obstacle avoidance impede direct negative gravitropic growth. Therefore, the polar KIPK and KIPKL1 kinases have different biological functions from the related AGC1 family kinases D6PK (D6 PROTEIN KINASE) or PAX (PROTEIN KINASE ASSOCIATED WITH BRX).

PMID:40261964 | DOI:10.1093/plcell/koaf056

Sci Signal. 2025 Apr 22;18(883):eads2547. doi: 10.1126/scisignal.ads2547. Epub 2025 Apr 22.

ABSTRACT

Adaptation to starvation is a multimolecular and temporally ordered process. We sought to elucidate how the healthy liver regulates various molecules in a temporally ordered manner during starvation and how obesity disrupts this process. We used multiomic data collected from the plasma and livers of wild-type and leptin-deficient obese (ob/ob) mice at multiple time points during starvation to construct a starvation-responsive metabolic network that included responsive molecules and their regulatory relationships. Analysis of the network structure showed that in wild-type mice, the key molecules for energy homeostasis, ATP and AMP, acted as hub molecules to regulate various metabolic reactions in the network. Although neither ATP nor AMP was responsive to starvation in ob/ob mice, the structural properties of the network were maintained. In wild-type mice, the molecules in the network were temporally ordered through metabolic processes coordinated by hub molecules, including ATP and AMP, and were positively or negatively coregulated. By contrast, both temporal order and coregulation were disrupted in ob/ob mice. These results suggest that the metabolic network that responds to starvation was structurally robust but temporally disrupted by the obesity-associated loss of responsiveness of the hub molecules. In addition, we propose how obesity alters the response to intermittent fasting.

PMID:40261956 | DOI:10.1126/scisignal.ads2547

PLoS Comput Biol. 2025 Apr 22;21(4):e1012925. doi: 10.1371/journal.pcbi.1012925. eCollection 2025 Apr.

ABSTRACT

Modern biological research is increasingly data-intensive, leading to a growing demand for effective training in biological data science. In this article, we provide an overview of key resources and best practices available within the Bioconductor project-an open-source software community focused on omics data analysis. This guide serves as a valuable reference for both learners and educators in the field.

PMID:40261894 | DOI:10.1371/journal.pcbi.1012925

Database (Oxford). 2025 Mar 21;2025:baaf020. doi: 10.1093/database/baaf020.

ABSTRACT

Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization on the one hand and flexibility on the other. In many instances of Breedbase, a digital ecosystem for plant breeding designed for genomic selection, the goal is to capture phenotypic data using highly curated and rigorous crop ontologies, while adapting to the specific requirements of plant breeders to record data quickly and efficiently. For example, post-composing enables users to tailor ontology terms to suit specific and granular use cases such as repeated measurements on different plant parts and special sample preparation techniques. To achieve this, we have implemented a post-composing tool based on orthogonal ontologies providing users with the ability to introduce additional levels of phenotyping granularity tailored to unique experimental designs. Post-composed terms are designed to be reused by all breeding programs within a Breedbase instance but are not exported to the crop reference ontologies. Breedbase users can post-compose terms across various categories, such as plant anatomy, treatments, temporal events, and breeding cycles, and, as a result, generate highly specific terms for more accurate phenotyping.

PMID:40261748 | DOI:10.1093/database/baaf020

Database (Oxford). 2025 Jan 22;2025:baae133. doi: 10.1093/database/baae133.

ABSTRACT

Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information systems. Most of these structures change over time, incorporating new knowledge or information that was previously missing. Managing these changes is a challenge, both in terms of communicating changes to users and providing mechanisms to make it easier for multiple stakeholders to contribute. To fill that need, we have created KGCL, the Knowledge Graph Change Language (https://github.com/INCATools/kgcl), a standard data model for describing changes to KGs and ontologies at a high level, and an accompanying human-readable Controlled Natural Language (CNL). This language serves two purposes: a curator can use it to request desired changes, and it can also be used to describe changes that have already happened, corresponding to the concepts of "apply patch" and "diff" commonly used for managing changes in text documents and computer programs. Another key feature of KGCL is that descriptions are at a high enough level to be useful and understood by a variety of stakeholders-e.g. ontology edits can be specified by commands like "add synonym 'arm' to 'forelimb'" or "move 'Parkinson disease' under 'neurodegenerative disease'." We have also built a suite of tools for managing ontology changes. These include an automated agent that integrates with and monitors GitHub ontology repositories and applies any requested changes and a new component in the BioPortal ontology resource that allows users to make change requests directly from within the BioPortal user interface. Overall, the KGCL data model, its CNL, and associated tooling allow for easier management and processing of changes associated with the development of ontologies and KGs. Database URL: https://github.com/INCATools/kgcl.

PMID:40261730 | DOI:10.1093/database/baae133

JCI Insight. 2025 Apr 22;10(8):e184544. doi: 10.1172/jci.insight.184544. eCollection 2025 Apr 22.

ABSTRACT

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases with strong female predominance. They are caused by T cell-mediated injury of hepatic parenchymal cells, but the mechanisms underlying this sex bias are unknown. Here, we investigated whether testosterone contributes to T cell activation in women with PBC. Compared with sex- and age-matched healthy controls (n = 23), cisgender (cis) women with PBC (n = 24) demonstrated decreased testosterone serum levels and proinflammatory CD4+ T cell profile in peripheral blood. Testosterone suppressed the expression of TNF and IFN-γ by human CD4+ T cells in vitro. In trans men receiving gender-affirming hormone therapy (GAHT) (n = 25), testosterone affected CD4+ T cell function by inhibiting Th1 and Th17 differentiation and by supporting the differentiation into regulatory Treg. Mechanistically, we provide evidence for a direct effect of testosterone on T cells using mice with T cell-specific deletion of the cytosolic androgen receptor. Supporting a role for testosterone in autoimmune liver disease, we observed an improved disease course and profound changes in T cell states in a trans man with AIH/primary sclerosing cholangitis (PSC) variant syndrome receiving GAHT. We here report a direct effect of testosterone on CD4+ T cells that may contribute to future personalized treatment strategies.

PMID:40260919 | DOI:10.1172/jci.insight.184544

Emerg Microbes Infect. 2025 Apr 22:2470998. doi: 10.1080/22221751.2025.2470998. Online ahead of print.

ABSTRACT

From 2020 to 2022, a pulmonary tuberculosis (PTB) active case finding project based on chest X-ray (CXR) examination was conducted targeting individuals aged ≥ 65 years old in Jiangshan County, Quzhou City. The current study used computer-aided detection (CAD) software (JF CXR-1 v2) to retrospectively analyze the CXR images and to estimate its potential capacity for identifying PTB cases. The information of notified microbiologically confirmed PTB among the participants were exported from the Tuberculosis Information Management System. A total of 49,919 subjects participated in the 2020 examinations. Of these, 40,741 and 39,185 completed the follow-up surveys in 2021 and 2022, respectively. The pooled prevalence of suspected PTB reported by radiologists was 1.21% (1,579/129,776), compared with 12.43% (16,129/129,776) reported by CAD. Of 101 bacteriologically confirmed PTB cases notified over three years, radiologists and CAD reported 45.54% (46/101) and 83.16% (84/101) as suspected cases, respectively. Among subjects with abnormal CAD (CAD score>0.35), the majority of the notified confirmed PTB patients (63/84) had their CAD scores >75% quantiles (as＞0.75). With 3 years' results, their CAD scores exhibited dynamic changes along with disease progression or treatment with median scores peaking in the year of diagnosis. This intriguing finding suggests that CAD for CXR reading assisted radiologists in PTB screening by reducing workload and improving case finding. The CAD primary score may have the potential to identify high-risk individuals and early PTB patients, adding a new dimension to our understanding of disease progression.

PMID:40260691 | DOI:10.1080/22221751.2025.2470998

Elife. 2025 Apr 22;13:RP101967. doi: 10.7554/eLife.101967.

ABSTRACT

Protein-protein interactions are fundamental to understanding the molecular functions and regulation of proteins. Despite the availability of extensive databases, many interactions remain uncharacterized due to the labor-intensive nature of experimental validation. In this study, we utilized the AlphaFold2 program to predict interactions among proteins localized in the nuage, a germline-specific non-membrane organelle essential for piRNA biogenesis in Drosophila. We screened 20 nuage proteins for 1:1 interactions and predicted dimer structures. Among these, five represented novel interaction candidates. Three pairs, including Spn-E_Squ, were verified by co-immunoprecipitation. Disruption of the salt bridges at the Spn-E_Squ interface confirmed their functional importance, underscoring the predictive model's accuracy. We extended our analysis to include interactions between three representative nuage components-Vas, Squ, and Tej-and approximately 430 oogenesis-related proteins. Co-immunoprecipitation verified interactions for three pairs: Mei-W68_Squ, CSN3_Squ, and Pka-C1_Tej. Furthermore, we screened the majority of Drosophila proteins (~12,000) for potential interaction with the Piwi protein, a central player in the piRNA pathway, identifying 164 pairs as potential binding partners. This in silico approach not only efficiently identifies potential interaction partners but also significantly bridges the gap by facilitating the integration of bioinformatics and experimental biology.

PMID:40259744 | DOI:10.7554/eLife.101967

Plant Physiol. 2025 Mar 28;197(4):kiaf095. doi: 10.1093/plphys/kiaf095.

ABSTRACT

Crassulacean acid metabolism (CAM) is an adaptation to environments where water availability is seasonal or extremely low. It serves to ensure plant survival and/or maintain productivity in these adverse environments. CAM has repeatedly evolved in many plant lineages, although it requires a large and complex set of enzymes, transporters, and regulatory processes to control metabolite flux and pools. To test the potential levels at which CAM is regulated, we analyzed the CAM plant Kalanchoë laxiflora and compared with the genomes and transcriptomes of other CAM plants across a wide phylogenetic range. We show that CAM-associated transcripts and proteins did not exhibit a binary on/off pattern in abundance between day and night in K. laxiflora. Instead, K. laxiflora and many CAM plants displayed shared amino acid changes among proteins compared to C3 plants, especially in starch metabolism. Phosphoproteomics identified differential phosphorylation in K. laxiflora proteins between day and night. Taken together, our results demonstrate that CAM photosynthesis is regulated at both the transcript and protein levels.

PMID:40259462 | DOI:10.1093/plphys/kiaf095

Microb Ecol. 2025 Apr 22;88(1):31. doi: 10.1007/s00248-025-02532-1.

ABSTRACT

Microbialites have the potential to record environmental changes and act as biosignatures of past geochemical conditions. As such, they could be used as indicators to decipher ancient rock records. Modern microbialites are primarily found in environments where competitors and destructors are absent or where biogeochemical conditions favor their continuous formation. Many previous studies have essentially focused on the role of photosynthetic microbes in controlling pH and carbonate speciation and potentially overlooked alternative non-photosynthetic pathways of carbonate precipitation. Given that microbial activity induces subtle geochemical changes, microbially induced carbonate precipitation (MICP) can involve several mechanisms, from extracellular polymeric substances (EPS), sulfate reduction, anaerobic oxidation of methane, to nitrogen cycling processes, such as ammonification, ureolysis, and denitrification. Moreover, the peritidal zone where temperate microbialites are mostly found today, is under the influence of both freshwater and seawater, arguing for successive biogeochemical processes leading to mineral saturation, and questioning interpretations of fossil records. This study investigates microbialites in three tide pools from the peritidal zone of Fongchueisha, Hengchun, Taiwan, to address the influence of salinity on microbial community composition and carbonate precipitation mechanisms. Microbial samples were collected across varying salinity gradients at multiple time points and analyzed using next-generation sequencing (NGS) of bacterial 16S and eukaryotic 18S rRNA genes. Our results indicate that dominant bacterial groups, including Cyanobacteria and Alphaproteobacteria, were largely influenced by salinity variations, albeit pH exhibited stronger correlation with community composition. Combining our results on geochemistry and taxonomic diversity over time, we inferred a shift in the trophic mode under high salinity conditions, during which the use of urea and amino acids as a nitrogen source outcompetes diazotrophy, ureolysis and ammonification of amino acids reinforcing carbonate precipitation dynamics by triggering an increase in both pH and dissolved inorganic carbon.

PMID:40259028 | DOI:10.1007/s00248-025-02532-1

Neurobiol Dis. 2025 Apr 19:106914. doi: 10.1016/j.nbd.2025.106914. Online ahead of print.

ABSTRACT

Huntington's Disease (HD) is caused by a CAG repeat expansion in the gene encoding Huntingtin (HTT). While normal HTT function appears impacted by the mutation, the specific pathways unique to CAG repeat expansion versus loss of normal function are unclear. To understand the impact of the CAG repeat expansion, we evaluated biological signatures of HTT knockout (HTT KO) versus those that occur from the CAG repeat expansion by applying multi-omics, live cell imaging, survival analysis and a novel feature- based pipeline to study cortical neurons (eCNs) derived from an isogenic human embryonic stem cell series (RUES2). HTT KO and the CAG repeat expansion influence developmental trajectories of eCNs, with opposing effects on the growth. Network analyses of differentially expressed genes and proteins associated with enriched epigenetic motifs identified subnetworks common to CAG repeat expansion and HTT KO that include neuronal differentiation, cell cycle regulation, and mechanisms related to transcriptional repression and may represent gain-of-function mechanisms that cannot be explained by HTT loss of function alone. A combination of dominant and loss-of-function mechanisms are likely involved in the aberrant neurodevelopmental and neurodegenerative features of HD that can help inform therapeutic strategies.

PMID:40258535 | DOI:10.1016/j.nbd.2025.106914

Proc Natl Acad Sci U S A. 2025 Apr 29;122(17):e2414342122. doi: 10.1073/pnas.2414342122. Epub 2025 Apr 21.

ABSTRACT

Genome modification is essential for studying and engineering bacteria, yet making efficient modifications to most species remains challenging. Bacteriophage-encoded single-stranded DNA-annealing proteins (SSAPs) can facilitate efficient genome editing by homologous recombination, but their typically narrow host range limits broad application. Here, we demonstrate that a single library of 227 SSAPs enables efficient genome-editing across six diverse bacteria from three divergent classes: Actinomycetia (Mycobacterium smegmatis and Corynebacterium glutamicum), Alphaproteobacteria (Agrobacterium tumefaciens and Caulobacter crescentus), and Bacilli (Lactococcus lactis and Staphylococcus aureus). Surprisingly, the most effective SSAPs frequently originated from phyla distinct from their bacterial hosts, challenging the assumption that phylogenetic relatedness is necessary for recombination efficiency, and supporting the value of a large unbiased library. Across these hosts, the identified SSAPs enable genome modifications requiring efficient homologous recombination, demonstrated through three examples. First, we use SSAPs with Cas9 in C. crescentus to introduce single amino acid mutations with >70% efficiency. Second, we adapt SSAPs for dsDNA editing in C. glutamicum and S. aureus, enabling one-step gene knockouts using PCR products. Finally, we apply SSAPs for multiplexed editing in S. aureus to precisely map the interaction between a conserved protein and a small-molecule inhibitor. Overall, this library-based SSAP screen expands engineering capabilities across diverse, previously recalcitrant microbes, enabling efficient genetic manipulation for both fundamental research and biotechnological applications.

PMID:40258142 | DOI:10.1073/pnas.2414342122

PLoS Comput Biol. 2025 Apr 21;21(4):e1012995. doi: 10.1371/journal.pcbi.1012995. Online ahead of print.

ABSTRACT

Over the past decade, pathogen genome sequencing has become well established as a powerful approach to study infectious disease epidemiology. In particular, when multiple genomes are available from several geographical locations, comparing them is informative about the relative size of the local pathogen populations as well as past migration rates and events between locations. The structured coalescent model has a long history of being used as the underlying process for such phylogeographic analysis. However, the computational cost of using this model does not scale well to the large number of genomes frequently analysed in pathogen genomic epidemiology studies. Several approximations of the structured coalescent model have been proposed, but their effects are difficult to predict. Here we show how the exact structured coalescent model can be used to analyse a precomputed dated phylogeny, in order to perform Bayesian inference on the past migration history, the effective population sizes in each location, and the directed migration rates from any location to another. We describe an efficient reversible jump Markov Chain Monte Carlo scheme which is implemented in a new R package StructCoalescent. We use simulations to demonstrate the scalability and correctness of our method and to compare it with existing software. We also applied our new method to several state-of-the-art datasets on the population structure of real pathogens to showcase the relevance of our method to current data scales and research questions.

PMID:40258093 | DOI:10.1371/journal.pcbi.1012995

PLoS Biol. 2025 Apr 21;23(4):e3003139. doi: 10.1371/journal.pbio.3003139. Online ahead of print.

ABSTRACT

During plant fertilization, excess male gametes compete for a limited number of female gametes. The dormant male gametophyte, encapsulated in the pollen grain, consists of two sperm cells enclosed in a vegetative cell. After reaching the stigma of a compatible flower, quick and efficient germination of the vegetative cell to a tip-growing pollen tube is crucial to ensure fertilization success. Rho of Plants (ROP) signaling and their activating ROP Guanine Nucleotide Exchange Factors (ROPGEFs) are essential for initiating polar growth processes in multiple cell types. However, which ROPGEFs activate pollen germination is unknown. We investigated the role of ROPGEFs in initiating pollen germination and the required cell polarity establishment. Of the five pollen-expressed ROPGEFs, we found that GEF8, GEF9, and GEF12 are required for pollen germination and male fertilization success, as gef8;gef9;gef12 triple mutants showed almost complete loss of pollen germination in vitro and had a reduced allele transmission rate. Live-cell imaging and spatiotemporal analysis of subcellular protein distribution showed that GEF8, GEF9, and GEF11, but not GEF12, displayed transient polar protein accumulations at the future site of pollen germination minutes before pollen germination, demonstrating specific roles for GEF8 and GEF9 during the initiation of pollen germination. Furthermore, this novel GEF accumulation appears in a biphasic temporal manner and can shift its location laterally. We showed that the C-terminal domain of GEF8 and GEF9 confers their protein accumulation and demonstrated that GEFs locally activate ROPs and alter Ca2+ levels, which is required for pollen tube germination. We demonstrated that not all GEFs act redundantly during pollen germination, and we described for the first time a polar domain with spatiotemporal flexibility, which is crucial for the de novo establishment of a polar growth domain within a cell and, thus, for pollen function and fertilization success.

PMID:40258071 | DOI:10.1371/journal.pbio.3003139

PLoS Comput Biol. 2025 Apr 21;21(4):e1012999. doi: 10.1371/journal.pcbi.1012999. Online ahead of print.

ABSTRACT

Cancer involves dynamic changes caused by (epi)genetic alterations such as mutations or abnormal DNA methylation patterns which occur in cancer driver genes. These driver genes are divided into oncogenes and tumor suppressors depending on their function and mechanism of action. Discovering driver genes in different cancer (sub)types is important not only for increasing current understanding of carcinogenesis but also from prognostic and therapeutic perspectives. We have previously developed a framework called Moonlight which uses a systems biology multi-omics approach for prediction of driver genes. Here, we present an important development in Moonlight2 by incorporating a DNA methylation layer which provides epigenetic evidence for deregulated expression profiles of driver genes. To this end, we present a novel functionality called Gene Methylation Analysis (GMA) which investigates abnormal DNA methylation patterns to predict driver genes. This is achieved by integrating the tool EpiMix which is designed to detect such aberrant DNA methylation patterns in a cohort of patients and further couples these patterns with gene expression changes. To showcase GMA, we applied it to three cancer (sub)types (basal-like breast cancer, lung adenocarcinoma, and thyroid carcinoma) where we discovered 33, 190, and 263 epigenetically driven genes, respectively. A subset of these driver genes had prognostic effects with expression levels significantly affecting survival of the patients. Moreover, a subset of the driver genes demonstrated therapeutic potential as drug targets. This study provides a framework for exploring the driving forces behind cancer and provides novel insights into the landscape of three cancer sub(types) by integrating gene expression and methylation data.

PMID:40258059 | DOI:10.1371/journal.pcbi.1012999