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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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Topological Closure Drives Structural Stabilization and Fast Cooperative Dynamics in Crowded Circular Polysomes

In linear polysomes, excluded-volume interactions among ribosomes can induce dimensional reduction of mRNA. Yet linear architectures allow steric stress to relax at open ends-- limiting how strongly crowding can remodel the mRNA's structure and dynamics. Using coarse-grained molecular-dynamics simulations, we compare circular and linear polysomes over a range of ribosome densities. Circular closure selects a predominantly quasi-planar global conformational ensemble, as indicated by a shape dimensionality dshape {approx} 2 over a range of ribosome densities. Crucially, circular topology and ribosome crowding act cooperatively to suppress structural fluctuations. While closure alone or linear crowding reduces relative global size fluctuations ({Delta}Rg/Rg) only to {approx} 0.16, their combined effect drives this fluctuation down to {approx} 0.07. Within this stabilized architecture, increasing ribosome density drives a distinct in-plane reorganization: the ring becomes more isotropic, global size fluctuations are strongly suppressed, and the scaling exponent increases toward {nu} [~=] 0.74 - 0.77, consistent with two-dimensional self-avoiding walk-like value over the accessible finite-size window, 1000 [≤] N [≤] 4969. Closure shortens the radius-of-gyration decorrelation time of circular polysomes by 40-fold relative to matched linear systems, reflecting the topological elimination of free ends. Within this closureselected ensemble, ribosome crowding further reduces the decorrelation time by up to 20% at the highest density. A fluctuation-informed crossover model links the density dependence of the global scaling exponent to inter-ribosomal subchain statistics. These results distinguish the geometric role of circular closure from the density-dependent steric response that it enables, revealing a confined yet dynamically responsive conformational regime for circular polysomes.

biophysics

GDNF enemas improve epithelial and immune defects in both aganglionic and ganglionic colon of Hirschsprung mice

Hirschsprung disease (HSCR) is a severe birth defect where ganglia of the enteric nervous system (ENS) are missing from distal bowel. The aganglionic segment is also characterized by increased epithelial permeability and pro-inflammatory immune activation. These problems may sequentially lead to translocation of gut microbes into the colon wall and systemic circulation, resulting in enterocolitis and sepsis. Current HSCR treatment via surgical resection of the aganglionic segment is lifesaving but not curative, often leaving patients with persistent gastrointestinal complications including recurrent risk of enterocolitis. As alternative, we are developing a regenerative medicine strategy based on in situ stimulation of tissue-resident ENS progenitors via rectal administration of the neurotrophic factor GDNF. Here, we report that GDNF-based therapy has pleiotropic gastrointestinal effects in a mouse model of short-segment HSCR, beyond its role in ENS regeneration. Interestingly, we found that these protective effects are not restricted to the aganglionic distal colon, also positively impacting the ENS-containing proximal colon. GDNF treatment reduces bacterial translocation both locally and in peripheral organs, and this is associated with recovery of the key epithelial junction proteins CLDN3, ZO1 and DSG2. Furthermore, multiparameter flow cytometry-based analysis of 55 lymphoid and 17 myeloid cell subtypes revealed that GDNF treatment has global anti-inflammatory effects, preferentially affecting innate over adaptive immunity. Overall, these findings highlight a critical role for GDNF treatment in reestablishing proper epithelial and immune cell homeostasis, offering promising therapeutic avenues not only for HSCR but also potentially for other intestinal disorders with overlapping pathophysiology.

developmental biology

Time-averaged and Time-varying Structure of the Gastric Network Revealed Through fMRI-Electrogastrogram Synchronization

The gastric network, comprised of brain regions whose activity synchronizes with the stomach's slow-wave rhythm, offers a unique window into the brain-body interaction involved in interoceptive processing. While previous work has established the existence of this network, its intrinsic organization and temporal unfolding remain poorly understood. Here, we reanalyzed resting-state fMRI-electrogastrogram data from 43 healthy adults of both sexes to characterize the time-averaged architecture and time-varying reconfiguration of the gastric network. We identified regions exhibiting phase-locked synchronization with the stomach slow electrical rhythm (0.05 Hz) and characterized cortical parcels comprising this network. Time-averaged graph-theoretical analysis revealed a fixed unimodal organization of functional communities, with primary visual, default mode network (DMN) and dorsal attention regions emerging as the principal time-averaged hubs. Next, we applied edge-centric functional connectivity (eFC) to capture the network state during transient high-amplitude "bursts". Time-varying community detection revealed communities whose compositions formed integrative combinations of DMN, visual, attentional and control elements. Edge-derived hubs shifted away from primary visual dominancy in the time-averaged analysis, and were instead directed by DMN regions, suggesting that moments of heightened connectivity in the network are coordinated by multisensory integration rather than passive sensory processing. These findings demonstrate that the gastric network is not merely a time-averaged, sensory-bound system, but rather a flexible and dynamically reconfiguring interoceptive network whose organization is selectively coordinated by transient cofluctuation events. This work provides a comprehensive network analysis of gastric-brain coupling and reveals a temporally structured mode of interoceptive integration that may support adaptive physiological and cognitive regulation.

neuroscience

Molecular basis of AMPA receptor labeling by ligand-directed acyl imidazole chemistry in living neurons

Rational design of covalent protein-labeling reagents in complex biological environments requires a molecular-level understanding of how the protein microenvironment governs chemical reactivity; yet, such mechanistic details remain inaccessible to experimental methods alone. In living neurons, Ligand-Directed Acyl Imidazole (LDAI) chemistry has been used to label AMPA receptors as a traceless, affinity-based protein labeling method. Although LDAI labeling reagents have been optimized in the lab, the atomic details of their interactions with the protein and the underlying mechanism remain elusive. In this work, we combined Quantum Mechanical (QM) calculations and molecular dynamics (MD) simulations to propose a detailed reaction mechanism for AMPAR labeling by LDAI reagents and to clarify how the protein microenvironment governs reactivity. Although Lys residues are usually protonated at physiological pH and therefore less nucleophilic in water, our QM results show that Lys labeling is energetically more favorable than competing reactions with Ser or water. MD simulations reveal that PFQX ---the LDAI reagent precursor--- binds dynamically to the GluA2 AMPAR as an antagonist, inducing conformational changes that reshape the local environment of the acyl imidazole (AI) warhead, underscoring that ligand identity strongly affects labeling outcomes. We also identified intra and intermolecular hydrogen bond networks that may contribute to further immobilize and pre-organize the LDAI reagent. Moreover, the probe's chemical nature shapes its interactions with the Ligand Binding Domain (LBD), offering a plausible rationale for the previously experimentally observed ligand-dependent fluorescent response. Taken together, our results establish design principles for exploiting the reagent geometry and binding pocket hydrogen-bonding networks for the rational design of LDAI reagents.

biophysics

Human Osteocytes Express MHC ClassII and Act as Non-classical Antigen-Presenting Cells During Bacterial Infection

Osteocytes are the most abundant cells in bone and are increasingly recognised not only for their role in skeletal remodelling and inflammatory signalling but also for their potential involvement in immune responses. In this study, we searched available gene expression datasets of human primary osteocyte-like cells exposed acutely to Staphylococcus aureus and identified significantly induced expression of key genes related to antigen processing and presentation. We then confirmed that human bone explant-derived osteoblastic cells, representative of a mature osteoblast-pre-osteocyte stage, expressed, as expected, high cell surface levels of major histocompatibility complex (MHC) Class I but also, low basal levels of the MHC Class II family member, HLA-DR. However, confocal imaging revealed high expression of MHC Class II molecules and the peptide-loading chaperone HLA-DM within the lysosomal compartments, consistent with canonical antigen-processing machinery. Differentiation towards a mature osteocyte phenotype increased MHC Class II protein levels and maintained expression of intracellular HLA-DM. Exposure of mature osteocyte-like cells to S. aureus further up-regulated both intracellular and cell surface MHC Class II expression. Demonstrative of antigen presenting cell functionality, S. aureus-exposed osteocytes induced autologous CD4+ T cell proliferation. Furthermore, MHC Class II expression in osteocytes was detected in bone sampled from patients with periprosthetic joint infections, providing evidence that these mechanisms operate in vivo. Together, our findings reveal that human osteocytes are capable of inducible MHC Class II-associated antigen presentation in response to bacterial challenge, pointing to a novel role for osteocytes in adaptive immune surveillance within bone.

immunology

Mind the gap between functional groups and surface of magnetic nanoparticles for highly specific magnetic-based protein assays in biological medium

Magnetic readout-based assays are compatible with unprocessed biological samples as unbound background molecules do not interfere with magnetic signal. Yet, a true challenge is their poor specificity and susceptibility of magnetic nanoparticles (MNPs) to clusters in complex biological media, hampering their true advancement. Here, we demonstrate that the spatial organization of functional groups at the external periphery of custom magnetic nanoparticles by harnessing ultra-dense double-stranded DNA results in an efficient antibody conjugation with good accessibility toward antigen. By labeling our MNPs with anti-S protein neutralizing IgG antibody, we showcase the detection of S1 subunit of SARS-CoV-2 Spike protein in a wash-free fashion in less than five minutes in nM regime using magnetic particle spectrometer. By mixing our IgG-labelled MNPs with DMEM cell culture (10-20% FBS serum), we sense the S1 proteins in a one-pot fashion with high specificity. Our results show that by having the ultra-dense dsDNA shell on MNPs, the entropic cost of an irreversible protein binding to particle surface is high, thus allowing the formation of dynamic protein corona on the DNA shell that can be replaced with S1 protein with high affinity. When the azide moieties are placed at the close proximity of MNPs by using non-functional dsDNA, antibody conjugation becomes inefficient, to a level not sufficient for S1 protein detection. Our study highlights the importance of spatial organization of functional moieties on the nanoscale on magnetic nanoparticles for highly specific assays in biologically complex media.

biochemistry

Inheritance of a Single Edited CD46 Allele Is Associated with Reduced Ex Vivo Susceptibility to Bovine Viral Diarrhea Virus

Bovine viral diarrhea virus (BVDV) remains an economically important pathogen of cattle despite widespread vaccination. A homozygous CD46-edited Gir heifer (Ginger) was previously shown to have significantly reduced susceptibility to BVDV. The edited allele contains an in-frame six amino acid substitution within the virus-binding domain of the BVDV entry receptor CD46, replacing residues G82QVLAL with A82LPTFS. Here, we investigated whether reduced BVDV susceptibility is maintained when the edited allele is inherited in the heterozygous state. Ginger was artificially inseminated with semen from an unedited Gir bull and produced a healthy heterozygous CD46-edited bull calf (Giraldo). Whole-genome sequencing confirmed the inheritance and structural integrity of Giraldo's edited allele. Compared with Ginger, Giraldo exhibited similarly reduced ex vivo BVDV susceptibility across primary fibroblasts, lymphocytes, and monocytes, despite inheriting a wild-type CD46 allele from the sire. Allele-specific CD46 RNA expression analysis demonstrated expression of both the edited and wild-type CD46 alleles. Thus, the reduced-susceptibility phenotype was not attributable to transcriptional silencing of the wild-type allele. Lentiviral complementation studies in CD46-knockout Madin-Darby bovine kidney (MDBK) cells further demonstrated that this wild-type CD46 allele was competent to support BVDV infection when expressed independently. Together, these findings indicate that the CD46 A82LPTFS allele can confer reduced BVDV susceptibility in the heterozygous state despite expression of a functional wild-type CD46 allele. This result suggests the potential to more rapidly disseminate reduced BVDV susceptibility through conventional breeding using homozygous CD46-edited sires.

molecular biology

Beyond Equilibrium Ensembles: Time Rescaling in Coarse-Grained Simulations across Single-Molecule and Condensate Regimes

Residue-level coarse-grained simulations provide a powerful route for modeling biomolecular condensates over length and time scales that are difficult to access with atomistic molecular dynamics. Coarse-grained models have been shown to reproduce many aspects of equilibrium phase behavior. However, it remains unclear to what extent such models can reproduce the relative timescales of molecular dynamics. Here, we examine this question for complex coacervates with markedly different dynamics, formed by the highly acidic intrinsically disordered protein prothymosin with four cationic partners: linker histone H1, protamine, polylysine, and polyarginine. Coexistence simulations using a residue-level coarse-grained model reproduce key equilibrium observables from experiments, including dense-phase concentrations, ionic-strength-dependent phase behavior, and chain dimensions in the dense and dilute phases. Dynamics are accelerated in these simulations, but a composition-specific time-rescaling factor captures the ionic-strength dependence of chain reconfiguration times within a given complex coacervate. In contrast, time rescaling is not transferable between dense and dilute phases or across condensate compositions and can depend on the chosen observable. These results show that agreement with measured equilibrium observables does not imply a universally transferable timescale for conformational dynamics in residue-level coarse-grained simulations. However, we find that the required time rescaling strongly correlates with the interaction energy of the protein chains, suggesting that the missing frictional effects arise from protein-protein interactions rather than solely from protein-solvent interactions, reminiscent of internal friction. Our findings highlight the need to combine thermodynamic validation with kinetic calibration when interpreting chain relaxation, molecular diffusion, and material properties from residue-level coarse-grained simulations of biomolecular condensates.

biophysics

From Bile Acids to a Gas-Producing Microbiome Phenotype: A Novel Mechanism of Host-Microbiome Communication

Background Microbiome-derived metabolites regulate host physiology, yet bacterial gaseous metabolites remain largely overlooked. Traditionally regarded as fermentation end-products, bacterial gases may act as biologically active mediators of host-microbiome communication. We hypothesized that bile acids regulate bacterial gaseous metabolism and influence host epithelial responses. Methods A high gas-producing clinical Escherichia coli isolate from a patient with moderately severe acute pancreatitis was cultured with selected primary and secondary bile acids. Gas production was assessed by pressure measurements, GC-TCD and GC-MS. Biological activity was evaluated by indirect exposure of Caco-2 and PANC-1 epithelial cells, followed by apoptosis/necrosis assays and whole-transcriptome RNA sequencing. Results Bile acids markedly reshaped bacterial gaseous metabolism. Cholic acid and deoxycholic acid promoted intense gas production, whereas chenodeoxycholic acid almost completely abolished it. Despite minimal apoptosis and necrosis, bacterial gaseous metabolites induced extensive transcriptional remodeling. Caco-2 cells showed stronger responses than PANC-1 cells, particularly to deoxycholic acid-derived gases, involving inflammatory signaling, extracellular matrix remodeling, epithelial plasticity, stress responses, and cancer-associated genes including PTGS2, MMP1, PLAUR, NR4A2, and SERPINE1. PANC-1 cells exhibited a more restricted response involving oxidative stress, proteostasis, and autophagy-associated pathways. Conclusions Our findings indicate that bacterial gases are a previously underrecognized class of microbiome-derived signaling molecules capable of modulating host gene expression independently of direct bacterial contact. We identify a gas-producing microbiome phenotype regulated by bile acid composition, linking microbial metabolism with epithelial signaling. These findings expand the concept of host-microbiome communication and provide a framework for investigating bacterial gaseous metabolites in intestinal and pancreatic diseases.

microbiology

From Public Archive to Reusable Resource: Characterizing Gut Microbiome Metadata in the NCBI SRA

Public sequencing repositories contain large amounts of gut microbiome data that could support cross-study comparison, reproducibility analysis, and microbiome foundation model development. However, the extent to which these data are structured, harmonized, and reusable at archive scale remains unclear. Here, we characterized publicly available gut microbiome sequencing metadata from the NCBI Sequence Read Archive using Google BigQuery, focusing on human gut metagenome, mouse gut metagenome, and broadly annotated gut metagenome records. We evaluated temporal growth, sequencing depth, BioSample and BioProject structure, platform and instrument use, metadata completeness, host attribution, publication linkage, and research themes from linked literature. Public gut microbiome data increased substantially over time and were dominated by human-associated datasets and Illumina sequencing platforms. Core technical metadata fields were highly complete, but biological context needed for reuse, including host identity, phenotype, study design, and disease status, was often inconsistently encoded or required recovery from BioSample attributes and linked publications. In the generic "gut metagenome" cohort, host identity could be assigned for only 13.00% of BioSamples, highlighting the limitations of broad organism annotations for automated cohort construction. Publication linkage was also incomplete at the archive level, although usable text was recovered for most linked publications. Topic modeling of SRA-linked literature showed persistent emphasis on core gut microbiota composition and increasing representation of human cohort and infant microbiome studies. Overall, these findings show that public gut microbiome data are extensive and technically rich but not uniformly analysis ready. Improved metadata harmonization, publication linkage, and biological context recovery will be necessary to support reliable large-scale reuse and AI-ready microbiome data resources.

bioinformatics

Resolving Heterogeneous Mechanical Domains via Physics-Aware Deep Clustering of Single-Molecule Force Spectroscopy Data

Many biological processes rely on mechanical forces, with protein molecules acting as key mediators. Understanding how proteins respond to mechanical stress is essential for conditions including cardiomyopathy and muscular dystrophy. Natural proteins such as dystrophin and utrophin are composed of heterogeneous folding domains with distinct mechanical properties; deciphering domain-level behavior provides insights into disease mechanisms and informs therapeutic strategies. Single-molecule force spectroscopy (SMFS) enables probing the mechanical properties of entire proteins, yet current approaches struggle to identify heterogeneous folding domains, particularly without prior knowledge. Here, we present the first automated framework to identify heterogeneous folding domains in SMFS data, applying both existing clustering methods and a novel physics-aware deep clustering architecture, LatentUnfold. LatentUnfold learns complementary latent representations from force magnitude and the force-extension physical relationship through dual autoencoders, jointly optimized for clustering assignments. We apply our framework to experimental SMFS data collected from a synthetic two-domain protein (ddFLN4-Titin I27) as well as natural protein constructs of dystrophin and utrophin, with Monte Carlo simulated datasets serving as controlled validation. For the synthetic protein, we recover mechanical properties consistent with previously reported values for each domain. For the natural proteins, we uncover two mechanically distinct domain populations - corresponding to the N-terminal domain and spectrin-like repeats - with differences in both unfolding force and contour length increase, and reveal different unfolding order between them for the first time. This work enables domain-level biological inference, overcoming prior limitations that relied on averaging and overlooked heterogeneity, thus advancing the understanding of mechanical behavior in protein unfolding.

biophysics

High-Throughput, automated assay for detection of colonization by Candida auris

Candida auris is an emerging multidrug-resistant fungal pathogen associated with healthcare-associated outbreaks, persistent colonization, and invasive infections. Increasing demand for surveillance has created a need for high-throughput methods capable of supporting large-scale screening programs. We developed and validated an automated laboratory-developed real-time PCR assay for detection of C. auris colonization on the Hologic Panther Fusion(R) open-access platform and compared its performance with the existing BD MAX assay. Analytical performance was evaluated by assessing limit of detection, accuracy, precision, specificity, inclusivity, reproducibility, and reagent and specimen stability. The Panther Fusion(R) assay demonstrated a limit of detection of approximately 18 CFU/reaction and showed 97% overall agreement with the BD MAX assay. Positive and negative percent agreement were 94% and 100%, respectively, with excellent agreement between methods ({kappa} = 0.94). No cross-reactivity was observed with non-C. auris organisms, all five major C. auris clades were detected, and assay performance remained stable across operators, reagent and specimen storage conditions. Following implementation, 26,838 clinical specimens were tested on the Panther Fusion(R) platform. Retrospective analysis demonstrated lower equivocal (0.28%) and indeterminate (0.09%) rates than those observed on the ABI and BD MAX platforms. Among PCR-positive specimens that underwent culture, the Panther Fusion(R) assay demonstrated 87.24% culture agreement. Because retrospective data were collected during different testing periods and patient populations, comparisons between platforms were not used to assess relative assay sensitivity or specificity. Implementation of the Panther Fusion(R) assay increased surveillance testing capacity from approximately 88 to 500 specimens per shift while maintaining robust analytical performance.

microbiology

CD36 phosphorylation alters the thrombospondin binding site and reduces internal cavity accessibility and volume

The cluster of differentiation 36 (CD36) is a membrane protein with broad physiological roles in health and disease, and its function is regulated in part by phosphorylation. Experimental evidence shows that phosphorylation of Thr92 reduces CD36 affinity for thrombospondin-1 (TSP-1), binding of which initiates antiangiogenic signaling, whereas phosphorylation of Ser237 decreases CD36-mediated fatty acid uptake, with implications for energy metabolism. However, the only available crystal structure of CD36 lacks phosphorylation, and the molecular mechanisms by which phosphorylation regulates CD36 function remain largely unknown. This study provides an atomically detailed computational characterization of CD36 in unphosphorylated and dual phosphorylated states, using molecular dynamics simulations with a total sampling time of 30 microseconds in combination with Markov state models. We present, to our knowledge, the first evidence of a cryptic pocket on CD36 surface that is formed by phosphorylation. This cryptic surface pocket and a loop spanning residues 121-131 form a high affinity binding site for TSP-1 derived ligands, shifting their binding away from the canonical site. We propose that this altered binding provides a molecular basis for the disruption of antiangiogenic signaling upon CD36 phosphorylation. Additionally, our data indicate that, phosphorylation increases helicity and compaction within the helix-loop region spanning residues 296-331, narrowing one of the entrances to the internal cavity and reducing its overall volume. These conformational changes provide a potential mechanistic explanation for the decrease in fatty acid uptake upon CD36 phosphorylation. Our findings provide structural insights that may inform the future design of CD36 modulators and emphasize the importance of targeting phosphorylation induced CD36 conformations in angiogenic and metabolic diseases.

biophysics

Sport expertise and motor imagery abilities shape sensorimotor rhythm modulations during visualisation tasks: Implications for neurofeedback-based cognitive training in athletes

Kinaesthetic motor imagery (kMI) is widely used in sport to enhance motor performance by engaging cortical sensorimotor networks. Neurofeedback may further support kMI, but the optimal neural target to reinforce remains unclear. Maximal sensorimotor event-related desynchronisation (SMR-ERD) represents a relevant target as it may index sensorimotor cortex engagement, yet sport expertise has been associated with reduced SMR-ERD, potentially reflecting neural efficiency. The optimal neurofeedback target may therefore depend on sport expertise, movement expertise, and individual kMI ability. This study examined how these factors influence sensorimotor activity during kMI. We compared 17 basketball players (Experts) and 16 individuals without formal basketball training (Novices). kMI ability and frequency of use were assessed using questionnaires, while SMR-ERD was quantified using electroencephalography (EEG) during kMI. Participants imagined either a basketball-specific movement (Free throw), for which only Experts had extensive experience, or a generic movement (Box lifting), familiar to both groups. Experts reported greater kMI ability and more frequent kMI use than Novices. Only Experts exhibited significant and sustained SMR-ERD during kMI. Moreover, SMR-ERD was stronger in Experts than Novices specifically during Free throw kMI, corresponding to their movement of expertise. Nonetheless, within the Expert group, higher kMI ability was associated with reduced SMR-ERD. These findings suggest that sport expertise initially enhances voluntary recruitment of sensorimotor networks during kMI, whereas greater kMI ability may subsequently promote neural efficiency, resulting in reduced overall sensorimotor cortical activation. These results highlight the need to tailor kMI-based neurofeedback training to users' sport expertise and kMI ability levels.

neuroscience

DNA Sequence-Programmed Protein Coronas Determine Intracellular Fate and Proteostatic Stress of Carbon Nanotubes

Single-walled carbon nanotubes (SWCNTs) show promise for optical biosensing, imaging, and drug delivery, but turning them into safe, precision nanomedicine tools requires understanding how nanotube surface chemistry dictates recognition and processing by cells. Like other nanomaterials, carbon nanotubes acquire a biomolecular corona on contact with biological fluids, and corona identity is increasingly recognized as central to sensor performance and drug delivery efficacy. However, whether corona identity also governs the intracellular fate of carbon nanotubes remains largely unknown. Here, we show that the single-stranded DNA wrapping of (6,5)-enriched single-walled carbon nanotubes reprograms their protein corona, intracellular trafficking, and macrophage response. By profiling (AT)15, (GT)15, and (CT)15 wrapped SWCNTs, we show that the wrapping sequence programs both the protein corona and the resulting proteostatic stress on macrophages. Photoluminescence imaging and confocal Raman measurements reported that (AT)15 is internalized the most yet leaves the proteome and nanotube structure largely undisturbed, whereas (CT)15, taken up the least, undergoes the most aggressive intracellular degradation and drives the highest oxidative and proteostatic stress. Corona proteomics indicated that all three tested nanotubes form coronas with distinct functional identities that are responsible for divergent intracellular routes. Time-resolved intracellular proteomics combined with functional assays resolved how the host cell reorganizes its biomolecular complexity over time, including oxidative outputs, aside from a sequence-independent core response involving particle engagement, phagosomal sorting, and lysosomal processing. These findings provide mechanistic insight into nanomaterial-cell interactions and the wrapping sequence as a tunable, nucleotide-level design handle for controlling the intracellular fate of carbon nanomaterials, with potential implications for safe and effective nanomedicine platforms.

bioengineering

Linoleic Acid-Lyso PG Axis promoting lipid droplet-mitochondria tethering by stabilizing Noncanonically Mitochondrial PPAR β/δ to Ameliorate Microglial Dysfunction in subarachnoid hemorrhage

Background Microglial lipid handling and mitochondrial failure contribute to brain injury after subarachnoid hemorrhage (SAH), but the lipid signals coupling these processes remain unclear. We investigated whether linoleic acid (LA) restores microglial homeostasis through lysophosphatidylglycerol 16:0 (LPG[16:0]) and peroxisome proliferator-activated receptor-{delta} (PPAR{delta}). Methods Cerebrospinal fluid metabolomics included 30 patients with aneurysmal SAH and 10 control participants. Mechanisms were examined in a blood-injection mouse model and hemoglobin-exposed primary mouse microglia using targeted lipidomics, RNA sequencing, mitochondrial and phagocytosis assays, pharmacological perturbation, fractionation, coimmunoprecipitation, thermal shift analysis, and structural modeling. Behavioral outcomes were evaluated by open-field, Y-maze, and Morris water-maze testing. Results; CSF LA was higher in SAH and discriminated the groups within this cohort (area under the curve, 0.9967 [95% CI, 0.9859-1.000]; P<0.001). LA attenuated inflammatory activation and restored phagocytosis, mitochondrial membrane potential, respiration, and ATP production in hemoglobin-exposed microglia. LA restored PLA2G15-associated LPG(16:0), which phenocopied these effects. Transcriptomic and inhibitor analyses identified PPAR{delta} as a downstream effector. LPG(16:0) increased PPAR{delta} stability, and fractionation and protease protection identified a PPAR{delta} pool on the cytosolic face of the outer mitochondrial membrane. PPAR{delta} associated with PLIN2 and CPT1A, promoted lipid droplet-mitochondria apposition, and supported fatty acid oxidation. In mice, LA reduced neuroinflammatory injury and partially improved anxiety-related behavior and spatial memory.

neuroscience

Glutaminase contributes to MYC-induced cell-autonomous autophagy and to RasV12-dependent non-autonomous autophagy in the Drosophila wing disc epithelium

MYC-driven metabolic reprogramming supports rapid cell growth but also creates metabolic demands that require adaptive mechanisms to maintain cellular homeostasis. Here, combining clonal analysis in Drosophila wing imaginal discs with studies in Schneider S2 cells, we identify glutamine metabolism as a component of Myc-induced autophagy. Myc increased the expression of genes involved in glutamine utilization, including glutaminase (GLS), and enhanced ammonia production, a metabolic by-product of glutaminolysis. Genetic depletion of GLS in clones suppressed the accumulation of Myc-induced Atg8a-positive structures and reduced autophagic flux, demonstrating that glutaminase contributes to the autophagic response elicited by Myc. Exogenous NHCl was sufficient to induce Atg8a-positive structures and partially restored their accumulation following GLS depletion, supporting ammonia as a downstream contributor to this response. Mechanistically, Myc-induced autophagy in clones required the core autophagy factor Atg5 but was not suppressed by depletion of Rheb or Atg1, consistent with an autophagic program that can operate independently of canonical TOR-Atg1 signaling. We further found that Myc activity is required for RasV12-driven epithelial overgrowth and that RasV12 cells induce a pronounced non-cell-autonomous accumulation of Atg8a-positive structures in wild-type cells surrounding RasV12 clones. Depletion of either Myc or GLS in RasV12 cells strongly reduced this neighboring autophagic response, linking Myc-dependent glutamine metabolism in transformed cells to autophagy in the surrounding tissue. Together, our findings identify GLS-dependent glutamine metabolism as a previously unrecognized component of Myc-induced autophagy and extend this relationship to Ras-transformed epithelia, where Myc and Gls contribute to non-cell-autonomous autophagic responses in neighboring cells.

cell biology

Rapid phase resetting of Aedes aegypti circadian rhythms by transient alterations in light exposure

Circadian clocks enable mosquitoes to anticipate recurring environmental variations and coordinate behaviors critical for survival and disease transmission, such as locomotion, reproduction, host-seeking, and blood-feeding, with times of day when performance is maximal. In Aedes aegypti, locomotor activity follows a robust diurnal rhythm shaped by endogenous circadian clocks and environmental cues, among which light has been shown to be the primary source of temporal information. While early studies established the role of light in regulating locomotor activity, behavior, oviposition and pupation, it remains unclear which features of a light cycle drive changes in circadian rhythms. This question is increasingly relevant as Ae. aegypti is frequently exposed to artificial and dynamic lighting conditions in urban environments. Here, we investigated how transient changes in light schedules influence circadian rhythms in locomotor activity by systematically manipulating the timing, duration, and direction of light exposure. Using a high-throughput assay, we tested over 1900 individuals, including wild-type and timeless knockout mutants, and showed that a single day of al tered lighting is sufficient to induce robust phase shifts, with no evidence of masking effects. A 6-hour light pulse was sufficient to re-entrain mosquitoes regardless of the timing of the pulse, and phase shifts were primarily driven by the offset time of the light pulse, indicating that light-offset acts as a major zeitgeber. Together, these findings challenge conventional assumptions about the timescale of circadian synchronization and highlight the remarkable plasticity of mosquito behavior in response to anthropogenic light. Eventually, these effects could explain the rapid adaptation of the species to urban environments and have potential consequences for disease transmission dynamics.

animal behavior and cognition