Biosens Bioelectron. 2025 Jan 13;273:117142. doi: 10.1016/j.bios.2025.117142. Online ahead of print.

ABSTRACT

Food allergies affect millions of individuals worldwide, significantly impacting personal health and the economy. While avoiding allergenic foods remains the primary management strategy, consumers lack reliable means for immediate allergen detection in everyday dining settings. Here, we present iEAT2 (integrated Exogenous Allergen Test 2), an advanced electrochemical sensing system for rapid, on-site food allergen detection. Building upon our previous assay system, the iEAT2 features technical breakthroughs: i) a complete kit for sample processing, including a torsion device for food grinding, and ii) a new strategy for multi-electrode measurements, which enables the simultaneous detection of multiple allergens in a simplified electronic architecture. We designed a compact iEAT2 prototype capable of 16 electrochemical reactions. Experimental validation confirmed the independent electrochemical measurements in a simultaneous operation. Furthermore, the entire testing protocol was completed within 15 min, from allergen extraction to detection. The platform detected three common food allergens (gliadin, Ara h1, and ovalbumin) at concentrations below established allergic reaction thresholds. It also effectively identified cross-contamination events in real-world food samples. This technology may empower consumers to monitor food safety and improve its management.

PMID:39832405 | DOI:10.1016/j.bios.2025.117142

NPJ Biosens. 2025;2(1):2. doi: 10.1038/s44328-024-00018-7. Epub 2025 Jan 16.

ABSTRACT

The reactivation of heterotrimeric protein phosphatase 2A (PP2A) through small molecule activators is of interest to therapeutic intervention due to its dysregulation, which is linked to chronic conditions. This study focuses on the PP2A scaffold subunit PR65 and a small molecule activator, ATUX-8385, designed to bind directly to this subunit. Using a label-free single-molecule approach with nanoaperture optical tweezers (NOT), we quantify its binding, obtaining a dissociation constant of 13.6 ± 2.5 μM, consistent with ensemble fluorescence anisotropy results but challenging to achieve with other methods due to low affinity. Single-molecule NOT measurements reveal that binding increases optical scattering, indicating PR65 elongation. This interpretation is supported by all-atom molecular dynamics simulations showing PR65 adopts more extended conformations upon binding. This work highlights NOT's utility in quantifying binding kinetics and structural impact, offering insights valuable for drug discovery.

PMID:39830999 | PMC:PMC11738983 | DOI:10.1038/s44328-024-00018-7

Iran J Pharm Res. 2024 Sep 15;23(1):e149463. doi: 10.5812/ijpr-149463. eCollection 2024 Jan-Dec.

ABSTRACT

BACKGROUND: Dry eye disease (DED) is a multifactorial condition characterized by ocular surface inflammation, tear film instability, and corneal epithelial damage. Current treatments often provide temporary relief without addressing the underlying inflammatory mechanisms.

OBJECTIVES: This study examined the therapeutic potential of crocin and nobiletin, two naturally derived compounds with well-known antioxidant and anti-inflammatory properties, in a mouse model of DED induced by lacrimal gland excision (LGE).

METHODS: Thirty female Balb/c mice were divided into five groups (n = 6 each): Control (sham surgery), untreated DED, nobiletin-treated DED (32.75 µM), crocin-treated DED (34 µM), and 1% betamethasone-treated DED. Treatments were administered three times daily for 28 days. Ocular tissues were evaluated using Hematoxylin and Eosin (H&E) staining and fluorescein staining. Conjunctival inflammatory cytokines, including interleukin-6 (IL-6), interleukin-1 beta (IL-1β), and tumor necrosis factor-alpha (TNF-α), were measured by enzyme-linked immunosorbent assay (ELISA).

RESULTS: Histological analysis showed that the crocin and nobiletin treatment groups exhibited reduced epithelial disruption, keratinization, and inflammatory cell infiltration compared to the untreated DED group. The ELISA assay revealed that both compounds efficiently inhibited the production of the pro-inflammatory cytokines IL-6, TNF-α, and IL-1β, which are key mediators of DED pathogenesis. Fluorescein staining further confirmed the protective impact of crocin and nobiletin on corneal epithelial integrity. Moreover, the anti-inflammatory and epithelial-preserving effects of these compounds were comparable to those of the corticosteroid betamethasone.

CONCLUSIONS: Overall, these findings suggest that crocin and nobiletin have therapeutic potential for DED management by modulating inflammatory responses and enhancing ocular surface healing. These naturally derived compounds offer promising avenues for the development of safer and more effective treatments for this challenging condition. However, further investigations, including clinical trials, are essential to elucidate the underlying mechanisms of action and optimize therapeutic approaches.

PMID:39830666 | PMC:PMC11742122 | DOI:10.5812/ijpr-149463

Natl Sci Rev. 2024 Dec 9;12(2):nwae441. doi: 10.1093/nsr/nwae441. eCollection 2025 Feb.

ABSTRACT

The enormous computational requirements and unsustainable resource consumption associated with massive parameters of large language models and large vision models have given rise to challenging issues. Here, we propose an interpretable 'small model' framework characterized by only a single core-neuron, i.e. the one-core-neuron system (OCNS), to significantly reduce the number of parameters while maintaining performance comparable to the existing 'large models' in time-series forecasting. With multiple delay feedback designed in this single neuron, our OCNS is able to convert one input feature vector/state into one-dimensional time-series/sequence, which is theoretically ensured to fully represent the states of the observed dynamical system. Leveraging the spatiotemporal information transformation, the OCNS shows excellent and robust performance in forecasting tasks, in particular for short-term high-dimensional systems. The results collectively demonstrate that the proposed OCNS with a single core neuron offers insights into constructing deep learning frameworks with a small model, presenting substantial potential as a new way for achieving efficient deep learning.

PMID:39830389 | PMC:PMC11737406 | DOI:10.1093/nsr/nwae441

ISME Commun. 2024 Dec 18;5(1):ycae164. doi: 10.1093/ismeco/ycae164. eCollection 2025 Jan.

ABSTRACT

Harmful Algal Blooms (HABs) of the toxigenic dinoflagellate Karenia brevis (KB) are pivotal in structuring the ecosystem of the Gulf of Mexico (GoM), decimating coastal ecology, local economies, and human health. Bacterial communities associated with toxigenic phytoplankton species play an important role in influencing toxin production in the laboratory, supplying essential factors to phytoplankton and even killing blooming species. However, our knowledge of the prevalence of these mechanisms during HAB events is limited, especially for KB blooms. Here, we introduced native microbial communities from the GoM, collected during two phases of a Karenia bloom, into KB laboratory cultures. Using bacterial isolation, physiological experiments, and shotgun metagenomic sequencing, we identified both putative enhancers and mitigators of KB blooms. Metagenome-assembled genomes from the Roseobacter clade showed strong correlations with KB populations during HABs, akin to symbionts. A bacterial isolate from this group of metagenome-assembled genomes, Mameliella alba, alleviated vitamin limitations of KB by providing it with vitamins B1, B7 and B12. Conversely, bacterial isolates belonging to Bacteroidetes and Gammaproteobacteria, Croceibacter atlanticus, and Pseudoalteromonas spongiae, respectively, exhibited strong algicidal properties against KB. We identified a serine protease homolog in P. spongiae that putatively drives the algicidal activity in this isolate. While the algicidal mechanism in C. atlanticus is unknown, we demonstrated the efficiency of C. atlanticus to mitigate KB growth in blooms from the GoM. Our results highlight the importance of specific bacteria in influencing the dynamics of HABs and suggest strategies for future HAB management.

PMID:39830096 | PMC:PMC11740886 | DOI:10.1093/ismeco/ycae164

ACS Omega. 2024 Dec 20;10(1):1419-1428. doi: 10.1021/acsomega.4c09036. eCollection 2025 Jan 14.

ABSTRACT

The human gut microbiota (HGM) is a complex ecosystem subtly dependent on the interplay between hundreds of bacterial species and numerous metabolites. Dietary phenols, whether ingested (e.g., plant-derived guaiacol, mequinol, or resveratrol) or products of bacterial fermentation (e.g., p-cresol), have been attributed with influencing bacterial growth and host health. They are cleared by phase II metabolism, one form utilizing β-d-glucuronidation, but encounter bacterially derived glucuronidases capable of hydrolyzing them to release their phenolic and glucuronic acid moieties with potential effects on host cells or the surrounding bacterial population. Tools to enable the detailed study of their activity are currently lacking. Syntheses of β-d-glucuronides from methyl 1,2,3,4 tetra-acetyl β-d-glucopyranosyluronate by direct glycosylation with 2-, 3-, or 4-methoxy- and 4-fluorophenol acceptors employing trimethylsilyl triflate catalysis are reported. Yields (methoxy series) were modest. An improved route from methyl 1,2,3,4-tetra-acetyl β-d-glucopyranosyluronate via selective anomeric deprotection (N-methyl piperazine) and conversion to an α-trichloroacetimidate glycosyl donor was employed. Coupling with 2- and 3-methoxyphenol acceptors and deprotection provided 2- and 3-methoxyphenyl β-d-glucuronides in 2-fold improved overall yield. These naturally occurring methoxyphenyl glucuronides augment available model substrates of dietary glucuronides, which include 3- and 4'-linked resveratrol. The use of model glucuronides as substrates was illustrated in studies of β-d-glucuronidase activity employing cell lysates of 9 species of HGM (Bacteroidetes), revealing distinct outcomes. Contrasting effects on bacterial growth were also observed between the free phenolic components, their respective glucuronides, and glucuronic acid. The glucuronide of 4-fluorophenol provided sensitive and background-free detection of β-glucuronidase activity using 19F NMR.

PMID:39829562 | PMC:PMC11740244 | DOI:10.1021/acsomega.4c09036

J Biol Chem. 2025 Jan 17:108206. doi: 10.1016/j.jbc.2025.108206. Online ahead of print.

ABSTRACT

It has been well established that adenosine plays a key role in the control of inflammation through G protein coupled receptors and recently shown that it can regulate thermogenesis. Here we investigated the specific requirements of the adenosine A2A receptor (A2AR) in mature adipocytes for thermogenic functionality and metabolic homeostasis. We generated fat tissue specific adenosine A2A receptor knock-out mice to assess the influence of signaling through this receptor on brown and beige fat functionality, obesity, insulin sensitivity, inflammation and liver function. Fat specific A2AR knock-out and wild type littermate mice were compared for potential differences in cold tolerance and energy metabolism. In addition, we measured glucose metabolism, AT inflammation and liver phenotypes in mice of the two genotypes after exposure to a diet rich in fat. Our results provide novel evidence indicating that loss of the adenosine A2A receptor specifically in adipocytes is associated with cold intolerance and decreased oxygen consumption. Furthermore, mice with fat specific ablation of the A2AR exposed to a diet rich in fat showed increased propensity to obesity, decreased insulin sensitivity, elevated adipose tissue inflammation and hepato-steatosis and -steatitis. Overall, our data provide novel evidence that A2AR in mature adipocytes safeguards metabolic homeostasis, suggesting the possibility of targeting this receptor selectively in fat for the treatment of metabolic disease.

PMID:39828097 | DOI:10.1016/j.jbc.2025.108206

N Biotechnol. 2025 Jan 17:S1871-6784(25)00006-8. doi: 10.1016/j.nbt.2025.01.005. Online ahead of print.

ABSTRACT

In order to improve predictability of outcome and reduce costly rounds of trial-and-error, machine learning models have been of increasing importance in the field of synthetic biology. Besides applications in predicting genome annotation, process parameters and transcription initiation frequency, such models have also been of help for pathway optimization. The latter is a common strategy in metabolic engineering and improves the production of a desirable compound by optimizing enzyme expression levels of the production pathway. However, engineering steps might not lead to sufficient improvement, and bottlenecks may remain hidden among the hundreds of metabolic reactions occurring in a living cell, especially if the production pathway is highly interconnected with other parts of the cell's metabolism. Here, we use the synthesis of chitooligosaccharides (COS) to show that the production from such complex pathways can be improved by using machine learning models and feature importance analysis to find new compounds with an impact on COS production. We screened Escherichia coli libraries of engineered transcription regulators with an expected broad range of metabolic diversity and trained several machine learning models to predict COS production titers. Subsequent feature analysis led to the finding of iron, whose addition we could show improved COS production in vivo up to 2-fold. Additionally, the analysis revealed important clues for future engineering steps.

PMID:39827984 | DOI:10.1016/j.nbt.2025.01.005

Comput Biol Med. 2025 Jan 18;186:109624. doi: 10.1016/j.compbiomed.2024.109624. Online ahead of print.

ABSTRACT

Studying and analysing the various phases and key proteins of cell cycles is essential for the understanding of cell development and differentiation. To this end, mechanistic models play an important role towards a system level understanding of the interactions between cell cycle components. Many quantitative models of cell cycles have been previously constructed using either stochastic or deterministic approaches. However, cell cycle models are inherently hybrid requiring the full and accurate interplay of the continuous system dynamics and their corresponding discrete events. Moreover, not all required experimental data are usually available when designing in-silico experiments for these scenarios. In this paper, we employ hybrid Petri nets to implement a hybrid model of the Caulobacter crescentus cell cycle. The model handles all required logics of cell cycles in a very elegant way. We then extend this model to support fuzzy kinetics for those parts where sufficient experimental data are not available and thus precise kinetic parameters cannot be estimated. With some of the kinetic parameters being set as fuzzy numbers, the model produces uncertain bands of outputs reflecting different possibilities of an output comprising most likely the correct one.

PMID:39827734 | DOI:10.1016/j.compbiomed.2024.109624

Nat Commun. 2025 Jan 18;16(1):825. doi: 10.1038/s41467-025-56077-5.

ABSTRACT

As next-generation sequencing technologies produce deeper genome coverages at lower costs, there is a critical need for reliable computational host DNA removal in metagenomic data. We find that insufficient host filtration using prior human genome references can introduce false sex biases and inadvertently permit flow-through of host-specific DNA during bioinformatic analyses, which could be exploited for individual identification. To address these issues, we introduce and benchmark three host filtration methods of varying throughput, with concomitant applications across low biomass samples such as skin and high microbial biomass datasets including fecal samples. We find that these methods are important for obtaining accurate results in low biomass samples (e.g., tissue, skin). Overall, we demonstrate that rigorous host filtration is a key component of privacy-minded analyses of patient microbiomes and provide computationally efficient pipelines for accomplishing this task on large-scale datasets.

PMID:39827261 | DOI:10.1038/s41467-025-56077-5

Sci Rep. 2025 Jan 18;15(1):2368. doi: 10.1038/s41598-024-83942-y.

ABSTRACT

Antarctic environments are dominated by microorganisms, which are vulnerable to viral infection. Although several studies have investigated the phylogenetic repertoire of bacteria and viruses in these poly-extreme environments with freezing temperatures, high ultra violet irradiation levels, low moisture availability and hyper-oligotrophy, the evolutionary mechanisms governing microbial immunity remain poorly understood. Using genome-resolved metagenomics, we test the hypothesis that Antarctic poly-extreme high-latitude microbiomes harbour diverse adaptive immune systems. Our analysis reveals the prevalence of prophages in bacterial genomes (Bacteroidota and Verrucomicrobiota), suggesting the significance of lysogenic infection strategies in Antarctic soils. Furthermore, we demonstrate the presence of diverse CRISPR-Cas arrays, including Class 1 arrays (Types I-B, I-C, and I-E), alongside systems exhibiting novel gene architecture among their effector cas genes. Notably, a Class 2 system featuring type V variants lacks CRISPR arrays, encodes Cas1 and Cas2 adaptation module genes. Phylogenetic analysis of Cas12 effector proteins hints at divergent evolutionary histories compared to classified type V effectors and indicates that TnpB is likely the ancestor of Cas12 nucleases. Our findings suggest substantial novelty in Antarctic cas sequences, likely driven by strong selective pressures. These results underscore the role of viral infection as a key evolutionary driver shaping polar microbiomes.

PMID:39827180 | DOI:10.1038/s41598-024-83942-y

Cell Rep Methods. 2025 Jan 15:100964. doi: 10.1016/j.crmeth.2024.100964. Online ahead of print.

ABSTRACT

We develop a data harmonization approach for C. elegans volumetric microscopy data, consisting of a standardized format, pre-processing techniques, and human-in-the-loop machine-learning-based analysis tools. Using this approach, we unify a diverse collection of 118 whole-brain neural activity imaging datasets from five labs, storing these and accompanying tools in an online repository WormID (wormid.org). With this repository, we train three existing automated cell-identification algorithms, CPD, StatAtlas, and CRF_ID, to enable accuracy that generalizes across labs, recovering all human-labeled neurons in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. This growing resource of data, code, apps, and tutorials enables users to (1) study neuroanatomical organization and neural activity across diverse experimental paradigms, (2) develop and benchmark algorithms for automated neuron detection, segmentation, cell identification, tracking, and activity extraction, and (3) share data with the community and comply with data-sharing policies.

PMID:39826553 | DOI:10.1016/j.crmeth.2024.100964

Cell Syst. 2025 Jan 16:S2405-4712(24)00402-2. doi: 10.1016/j.cels.2024.12.008. Online ahead of print.

ABSTRACT

The human gut microbiome contains many bacterial strains of the same species ("strain-level variants") that shape microbiome function. The tremendous scale and molecular resolution at which microbial communities are being interrogated motivates addressing how to describe strain-level variants. We introduce the "Spectral Tree"-an inferred tree of relatedness built from patterns of co-evolutionary constraint between greater than 7,000 diverse bacteria. Using the Spectral Tree to describe over 600 diverse gut commensal strains that we isolated, whole-genome sequenced, and metabolically profiled revealed (1) widespread phylogenetic structure among strain-level variants, (2) the origins of subspecies phylogeny as a shared history of phage infections across humans, and (3) the key role of inter-human strain variation in predicting strain-level metabolic qualities. Overall, our work demonstrates the existence and metabolic importance of structured phylogeny below the level of species for commensal gut bacteria, motivating a redefinition of individual strains according to their evolutionary context. A record of this paper's transparent peer review process is included in the supplemental information.

PMID:39826551 | DOI:10.1016/j.cels.2024.12.008

STAR Protoc. 2025 Jan 16;6(1):103570. doi: 10.1016/j.xpro.2024.103570. Online ahead of print.

ABSTRACT

Analyzing host-microbe interactions is essential for understanding how microbiota changes disrupt host homeostasis. Here, we present a protocol for predicting host-microbe protein-protein interactions and their downstream effects using MicrobioLink. We describe steps for setting up the environment, installing software, and preparing human transcriptomic and bacterial proteomic data. The protocol outlines procedures for predicting protein-protein interactions through domain-motif interactions, integrating multi-omic datasets to map downstream effects, performing network analyses to identify key regulatory pathways, and visualizing multi-layered networks for systems-level data interpretation. For complete details on the use and execution of this protocol, please refer to Gul et al.1 and Poletti et al.2.

PMID:39826120 | DOI:10.1016/j.xpro.2024.103570

Epigenetics. 2025 Dec;20(1):2453275. doi: 10.1080/15592294.2025.2453275. Epub 2025 Jan 18.

ABSTRACT

Menstrual effluent cell profiles have potential as noninvasive biomarkers of female reproductive and gynecological health and disease. We used DNA methylation-based cell type deconvolution (methylation cytometry) to identify cell type profiles in self-collected menstrual effluent. During the second day of their menstrual cycle, healthy participants collected menstrual effluent using a vaginal swab, menstrual cup, and pad. Immune cell proportions were highest in menstrual cup samples, and epithelial cells were highest in swab samples. Our work demonstrates the feasibility and utility of menstrual effluent cell profiling in population-level research using remotely collected samples and DNA methylation.

PMID:39825876 | DOI:10.1080/15592294.2025.2453275

Acta Physiol (Oxf). 2025 Feb;241(2):e14276. doi: 10.1111/apha.14276.

ABSTRACT

AIM: Long QT syndrome (LQTS) and catecholaminergic polymorphism ventricular tachycardia (CPVT) are inherited cardiac disorders often caused by mutations in ion channels. These arrhythmia syndromes have recently been associated with calmodulin (CaM) variants. Here, we investigate the impact of the arrhythmogenic variants D131E and Q135P on CaM's structure-function relationship. Our study focuses on the L-type calcium channel Cav1.2, a crucial component of the ventricular action potential and excitation-contraction coupling.

METHODS: We used circular dichroism (CD), 1H-15N HSQC NMR, and trypsin digestion to determine the structural and stability properties of CaM variants. The affinity of CaM for Ca2+ and interaction of Ca2+/CaM with Cav1.2 (IQ and NSCaTE domains) were investigated using intrinsic tyrosine fluorescence and isothermal titration calorimetry (ITC), respectively. The effect of CaM variants of Cav1.2 activity was determined using HEK293-Cav1.2 cells (B'SYS) and whole-cell patch-clamp electrophysiology.

RESULTS: Using a combination of protein biophysics and structural biology, we show that the disease-associated mutations D131E and Q135P mutations alter apo/CaM structure and stability. In the Ca2+-bound state, D131E and Q135P exhibited reduced Ca2+ binding affinity, significant structural changes, and altered interaction with Cav1.2 domains (increased affinity for Cav1.2-IQ and decreased affinity for Cav1.2-NSCaTE). We show that the mutations dramatically impair Ca2+-dependent inactivation (CDI) of Cav1.2, which would contribute to abnormal Ca2+ influx, leading to disrupted Ca2+ handling, characteristic of cardiac arrhythmia syndromes.

CONCLUSIONS: These findings provide insights into the molecular mechanisms behind arrhythmia caused by calmodulin mutations, contributing to our understanding of cardiac syndromes at a molecular and cellular level.

PMID:39825574 | DOI:10.1111/apha.14276

Genome Med. 2025 Jan 17;17(1):5. doi: 10.1186/s13073-025-01432-w.

ABSTRACT

BACKGROUND: Despite extensive analysis, the dynamic changes in prostate epithelial cell states during tissue homeostasis as well as tumor initiation and progression have been poorly characterized. However, recent advances in single-cell RNA-sequencing (scRNA-seq) technology have greatly facilitated studies of cell states and plasticity in tissue maintenance and cancer, including in the prostate.

METHODS: We have performed meta-analyses of new and previously published scRNA-seq datasets for mouse and human prostate tissues to identify and compare cell populations across datasets in a uniform manner. Using random matrix theory to denoise datasets, we have established reference cell type classifications for the normal mouse and human prostate and have used optimal transport to compare the cross-species transcriptomic similarities of epithelial cell populations. In addition, we have integrated analyses of single-cell transcriptomic states with copy number variants to elucidate transcriptional programs in epithelial cells during human prostate cancer progression.

RESULTS: Our analyses demonstrate transcriptomic similarities between epithelial cell states in the normal prostate, in the regressed prostate after androgen-deprivation, and in primary prostate tumors. During regression in the mouse prostate, all epithelial cells shift their expression profiles toward a proximal periurethral (PrU) state, demonstrating an androgen-dependent plasticity that is restored to normal during androgen restoration and gland regeneration. In the human prostate, we find substantial rewiring of transcriptional programs across epithelial cell types in benign prostate hyperplasia and treatment-naïve prostate cancer. Notably, we detect copy number variants predominantly within luminal acinar cells in prostate tumors, suggesting a bias in their cell type of origin, as well as a larger field of transcriptomic alterations in non-tumor cells. Finally, we observe that luminal acinar tumor cells in treatment-naïve prostate cancer display heterogeneous androgen receptor (AR) signaling activity, including a split between AR-positive and AR-low profiles with similarity to PrU-like states.

CONCLUSIONS: Taken together, our analyses of cellular heterogeneity and plasticity provide important translational insights into the origin and treatment response of prostate cancer. In particular, the identification of AR-low tumor populations suggests that castration-resistance and predisposition to neuroendocrine differentiation may be pre-existing properties in treatment-naïve primary tumors that are selected for by androgen-deprivation therapies.

PMID:39825401 | DOI:10.1186/s13073-025-01432-w

Nat Struct Mol Biol. 2025 Jan 17. doi: 10.1038/s41594-024-01474-5. Online ahead of print.

ABSTRACT

Lysosomal membrane protein LYCHOS (lysosomal cholesterol signaling) translates cholesterol abundance to mammalian target of rapamycin activation. Here we report the 2.11-Å structure of human LYCHOS, revealing a unique fusion architecture comprising a G-protein-coupled receptor (GPCR)-like domain and a transporter domain that mediates homodimer assembly. The NhaA-fold transporter harbors a previously uncharacterized intramembrane Na+ pocket. The GPCR-like domain is stabilized, by analogy to canonical GPCRs, in an inactive state through 'tethered antagonism' by a lumenal loop and strong interactions at the cytosol side preventing the hallmark swing of the sixth transmembrane helix seen in active GPCRs. A cholesterol molecule and an associated docosahexaenoic acid (DHA)-phospholipid are entrapped between the transporter and GPCR-like domains, with the DHA-phospholipid occupying a pocket previously implicated in cholesterol sensing, indicating inter-domain coupling via dynamic lipid-protein interactions. Our work provides a high-resolution framework for functional investigations of the understudied LYCHOS protein.

PMID:39824977 | DOI:10.1038/s41594-024-01474-5

Nat Commun. 2025 Jan 17;16(1):779. doi: 10.1038/s41467-025-56198-x.

NO ABSTRACT

PMID:39824823 | DOI:10.1038/s41467-025-56198-x

Dev Cell. 2025 Jan 10:S1534-5807(24)00778-0. doi: 10.1016/j.devcel.2024.12.039. Online ahead of print.

ABSTRACT

Embryonic wounds repair rapidly, with no inflammation or scarring. Embryonic wound healing is driven by collective cell movements facilitated by the increase in the volume of the cells adjacent to the wound. The mechanistic target of rapamycin (mTor) complex 1 (TORC1) is associated with cell growth. We found that disrupting TORC1 signaling in Drosophila embryos prevented cell volume increases and slowed down wound repair. Catabolic processes, such as autophagy, can inhibit cell growth. Five-dimensional microscopy demonstrated that the number of autophagosomes decreased during wound repair, suggesting that autophagy must be tightly regulated for rapid wound healing. mTor inhibition increased autophagy, and activating autophagy prevented cell volume expansion and slowed down wound closure. Finally, reducing autophagy in embryos with disrupted TORC1 signaling rescued cell volume changes and rapid wound repair. Together, our results show that TORC1 activation upon wounding negatively regulates autophagy, allowing cells to increase their volumes to facilitate rapid wound healing.

PMID:39824179 | DOI:10.1016/j.devcel.2024.12.039