Biology subjects

Zhang, R.

Publications and source records attributed to Zhang, R..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Inferring Cell Differentiation Dynamics with Unobserved Progenitors

A cell differentiation map describes the transitions between cell types during a developmental process, and determining this map is a key challenge in developmental biology. Recent single-cell lineage tracing technologies generate lineage trees that describe the history of cell divisions during a developmental process but do not directly measure differentiation events between cell types. Current approaches to infer cell differentiation maps from cell lineage trees make unrealistic assumptions about the developmental process, do not allow for unobserved progenitor cell types, or do not infer cell-type specific rates of growth and transitions. To address these issues, we introduce TROUPE, a likelihood-based framework that infers differentiation and growth dynamics directly from leaf-labeled cell lineage trees while allowing for unobserved progenitor types via biologically motivated potency constraints. We provide an efficient algorithm for computing the maximum likelihood transition and growth rates, as well as a simple model-selection scheme to choose the number of unobserved types. On simulations, TROUPE recovers transition and growth rates better than previous approaches even when there are unobserved types. We apply TROUPE to a model of mammalian development, Trunk-Like Structures (TLS), and show that TROUPE computes reasonable rates of self-renewal and differentiation in both standard and perturbed conditions.

developmental biology↗

bioRxiv2025

Acute in vivo proximity labeling for membrane targeted proteomics in neuronal circuits

MOTIVATIONDespite the growing use of proximity labeling tools, there are limited techniques available to identify subcellularly localized proteins within targeted neuronal circuits on acute timescales in vivo. We engineered membrane targeted versions of the proximity labeling enzyme TurboID and validated their use for proteomic discovery in the mouse brain. We optimized an in vivo protocol to identify proteins in cell bodies and long range neuronal projections, and proteins differentially detected during acute drug labeling windows. SUMMARYA major goal within molecular systems neuroscience is to bridge the study of neuronal circuit function with changes in protein expression and localization in awake behaving animals. However, there are limited tools for capturing changes in subcellularly-defined proteomes within neuronal circuits during activity-gated timescales in vivo. Here, we engineered targeted versions of the proximity labeling enzyme TurboID, to tag proteins at the neuronal membrane during a user-delivered biotin injection. We optimized a labeling strategy that enables a one-to-two-hour labeling window and tagged proteins in medial prefrontal cortex (mPFC) cell bodies and corresponding axons in a downstream projection. We performed proteomics to identify proteins enriched in mPFC cell bodies and terminals, and upregulated in mPFC cell bodies following an acute cocaine injection. These advancements enable the detection of proteins at the subcellular level within short labeling windows, allowing identification of stimulus-specific proteomes in behaving mice.

neuroscience↗

bioRxiv2025

Distinguishing near- versus off-critical phase behaviors of intrinsically disordered proteins

Intrinsically disordered prion-like low complexity domains (PLCDs) drive phase transitions that underlie the biogenesis of different biomolecular condensates. The mapping of critical points is essential for generating quantitative assessments of driving forces and for distinguishing phase behaviors in the critical versus off-critical regimes. Computations play an important role in connecting the molecular-scale interactions to mesoscale phase behaviors of PLCDs and other intrinsically disordered proteins. We report results from accurate mapping of the critical regime for an archetypal PLCD. This is achieved by combining large-scale simulations with computations of Binder cumulants and the use of rigorous finite-size scaling approaches. The computed binodal, defined by knowledge of the critical point and intersection of the left arm of the binodal by the overlap and percolation lines, can be demarcated into three distinct regimes. Regime I is farthest from the critical point, with the coexisting dilute phase being akin to a gas of dispersed polymers. Regime II lies above the intersection of the overlap line and the dilute arm of the binodal. Here, coexisting dilute phases are characterized by heterogeneous cluster-size distributions with heavy tails. In Regimes I and II, dense phases are confined percolated networks. Regime III is closest to the critical point. Here, the dense phase becomes unconfined and the percolated network swells to become system-spanning. Thus, Regime III comprises two interconnected, system-spanning networks. In addition to accurately mapping the critical point, we also evaluated methods for identifying the theta temperature. We find that conventional scaling approaches lead to erroneously low estimates of the theta temperature. Instead, accurate estimation of the theta temperature requires direct calculation of the temperature dependence of the two-body interaction coefficient. We discuss the broader implications of these findings for inferring solvent quality from scaling analyses.

biophysics↗

bioRxiv2025

A Functional Resting-State Network Atlas Based on 420 Older Adults with Hypertension

The Risk Reduction for Alzheimers Disease (rrAD) trial included 513 cognitively normal, sedentary, hypertensive older adults (aged 60 to 85 years) with dementia risk factors. We utilized 420 high-quality baseline resting-state functional MRI (rs-fMRI) scans from this cohort to develop a functional atlas tailored for aging populations. Typical rs-fMRI atlases derived from healthy young adults do not account for age-related changes, such as cortical atrophy, enlarged ventricles, and altered connectivity. To address this gap, we created a cohort-specific MNI-adjacent anatomical template, rrAD420, using SPM12s DARTEL registration. In this space, we derived a comprehensive functional atlas using both group independent component analysis (GICA) and probabilistic functional mode decomposition (PROFUMO). The rrAD420 atlas offers detailed representations of Resting-State Network (RSN) connectivity, encompassing unique configurations and overlapping interactions. It features two Default-Mode Network (DMN)-specific seed-based maps (DMN24 with cerebellum, DMN18 without) and data-driven components resembling the major RSNs. Furthermore, PROFUMO allowed for the identification of multimodal and combinatory networks, capturing connections within and between RSNs. While optimized for hypertensive older adults, the rrAD420 atlas serves as a versatile tool for broader aging populations, aiding in the study of neurodegenerative processes and biomarker discovery.

neuroscience↗

bioRxiv2025

Integrative spatial multi-omics reveals prognostic tumor niches in female genital tumors

Female genital tumors (FGTs), including ovarian, endometrial, and cervical cancers, pose a major global health challenge, yet their spatial and molecular determinants of progression and therapy resistance remain poorly understood. Here we present a large-scale integrative spatial and multi-omics atlas of FGTs, combining exome, transcriptome, methylome, and miRNA sequencing with high-resolution Visium HD spatial transcriptomics, profiling over 62 million cells from 100 tumors. We show that HPV-driven suppression of TGF{beta} signaling in cervical cancer disrupts myofibroblast (myCAF) formation and reshapes immune infiltration, while serous tumors exhibit extensive oncogene amplifications that activate MYC and PI3K pathways, linking chromosomal instability (CIN) to proliferative, immune-cold phenotypes. In high-grade serous ovarian cancer, we identify a previously unrecognized malignant domain, the Proliferating Core Desert (PCD) niche, defined by CIN-high epithelial enrichment, immune exclusion, stromal protection, and chemotherapy resistance, maintained through crosstalk with macrophages and fibroblasts. Finally, we develop POWER, a pathology foundation model that predicts PCD niche abundance from routine H&E slides, enabling robust stratification of prognosis and anti-angiogenic therapy response.

genomics↗

bioRxiv2025

In vitro Isolation and Identification of Metarhizium pinghaense Isolates and Assessment of Their Virulence against Whiteflies and Aphids

Four entomopathogenic fungal isolates were obtained from soil samples collected in Shouguang City, Shandong Province, using yellow mealworms as the baits. The result derived from the morphological and molecular identification of and assessment of the virulence against whiteflies (Bemisia tabaci) and the 4th instar aphids (Aphis gossypii) confirmed all four isolates as Metarhizium pinghaense, named SG-A, SG-B, SG-C, and SG-D, respectively. they were able to infect B. tabaci and A. gossypii with some differences in virulence and parasitic duration. The cumulative corrected mortality rates of B. tabaci and A. gossypii treated with the SG-A spore suspension (1x108 conidia/ml.) were 94.44% and 96.67%, respectively in 8 days after inoculation. The LC50 and LT50 of SG-A against B. tabaci and A. gossypii were 7.00x104, 4.21x105 (conidia/ml), 4.13 and 2.61 (days) respectively. Moreover, SG-C was more pathogenic to B. tabaci than to A. gossypii, but SG-B and SG-D were less virulent to both insects. In conclusion, M. pinghaense SG-A is highly pathogenic and greatly lethal against both A. gossypii and B. tabaci and should be used as a potential biocontrol agent to control whiteflies and aphids at their nymph stage during the vegetable production season.

microbiology↗

bioRxiv2025

IRCAS: a novel end-to-end approach to identify, rectify and classify comprehensive alternative splicing events in a transcriptome without genome reference

Alternative splicing (AS) is a fundamental post-transcriptional mechanism that amplifies proteomic diversity and enables adaptive responses across eukaryotes. Current AS detection methods rely heavily on reference genomes, limiting their applicability to non-model organisms. Existing reference-free approaches suffer from inaccurate splice site prediction and treat detection and classification as separate processes, resulting in cascading errors. We present IRCAS, an integrated end-to-end framework for reference-free AS analysis, comprising three modules: identification, rectification, and classification. IRCAS employs colored de Bruijn graphs for AS detection, an attention-based CNN for splice site rectification, and a hybrid Graph Neural Network combining GAT and Transformer layers for classification. Evaluation across four species demonstrates substantial improvements: splice site accuracy increased to 92-96% versus 50-55% for existing methods, and end-to-end accuracy reached 83.4% compared to 41.2% for the previous best method. IRCAS establishes a new benchmark for reference-free AS detection in non-model organisms. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=167 SRC="FIGDIR/small/689457v1_fig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1162531org.highwire.dtl.DTLVardef@e3c2e2org.highwire.dtl.DTLVardef@10f9032org.highwire.dtl.DTLVardef@c3cb5e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig 1.C_FLOATNO Workflow for construction and application of IRCAS. IRCAS is composed of three parts: identification, rectification, classification. (A) Workflow for reference-free AS identification from a raw transcriptomic data. First, according to the input transcripts, we apply BLAST all versus all alignment for preliminary screen. Then we adopt the MkcDBGAS Graph construction strategy. A cDBG was constructed from two sequences using a specified k-mer size. Based on bubble topologies, bubbles were classified into 5 types: SNV-induced, four AS-induced, MX-induced, AL-induced, AF-induced. (B)Workflow for AS position offset rectification and reconstruction of cDBG. Input transcript pairs are converted into a single sequence that includes two virtual nucleotides denoting the splicing start and end sites. SUPPA, a reference-based method, is utilized to determine the true splicing sites. The sequence is encoded into an nx6 vector using one-hot encoding. The offset between the true and predicted splicing sites is calculated and encoded as the ground truth. An attention-based convolutional neural network (CNN) rectification model is trained on these data to predict the offset, enabling the reconstruction of the cDBG with corrected splicing positions. (C) Workflow for 4 types AS classification. For each cDBG, node features, edge features, and global features are extracted. These features are integrated into distinct layers of a graph attention network (GAT)-Transformer hybrid model. This architecture enables high-precision classification of four types of AS events. (D)Workflow for end-to-end application of IRCAS. Transcriptomic data from any species lacking a reference genome is processed by IRCAS, enabling the classification of seven AS types with high accuracy. C_FIG

bioinformatics↗

bioRxiv2025

APOE E4 Alzheimer's Risk Converges on an Oligodendrocyte Subtype in the Human Entorhinal Cortex

The entorhinal cortex (ERC) is implicated in early progression of Alzheimers disease (AD). Here we investigated the impact of established biological risk factors for AD, including APOE genotype (E2 versus E4 alleles), sex, and ancestry, on gene expression in the human ERC. We generated paired spatially-resolved transcriptomics (SRT) and single-nucleus RNA sequencing data (snRNA-seq) in postmortem human ERC tissue from middle aged brain donors with no history of AD. APOE-dependent changes in gene expression predominantly mapped to a transcriptionally-defined oligodendrocyte subtype, which varied substantially with ancestry, and suggested differences in oligodendrocyte differentiation and myelination. Integration of SRT and snRNA-seq data identified a common gene expression signature associated with APOE genotype, which we localized to the same oligodendrocyte subtype and a white matter spatial domain. This suggests that AD risk in ERC may be associated with disrupted oligodendrocyte function, potentially contributing to future neurodegeneration. Lay SummaryAlzheimers disease (AD) is a neurodegenerative disorder that accounts for 60-80% dementia cases. Apolipoprotein E (APOE) genotype is the strongest genetic risk factor for AD, and the entorhinal cortex (ERC) is a brain region implicated in its earliest progression. Our study investigated how APOE genotype impacts gene expression in the ERC. We identified genotype-dependent effects on oligodendrocytes with different transcriptional profiles related to maturation that may help explain how APOE genotype mediates its effects on AD risk.

neuroscience↗

bioRxiv2025

Autolamellasomes: An Autophagy-Dependent Parallel Pathway for Bulk ER Degradation and Lysosome Biogenesis

Lysosomes containing multilamellar membrane whorls are a hallmark of cellular aging and storage disorders, yet the biogenesis of these structures has remained elusive for decades. Here, we identify a distinct form of endoplasmic reticulum (ER) remodeling, termed autolamellasomes, which mediates bulk ER degradation under chronic mTOR inhibition. Unlike canonical ER-phagy, autolamellasomes are concentric ER stacks that form via an autophagy-dependent but receptor-independent mechanism. Using Cryo-ET, CLEM, and a reconstituted cell-free system, we demonstrate that these structures arise from the cytosolic compaction of fragmented ER membranes, driven by the core autophagy machinery. We find that autolamellasomes accumulate in senescent cells and fibroblasts from patients with Hutchinson-Gilford progeria syndrome, linking sustained mTOR suppression to lysosomal membrane homeostasis. Our results resolve the origin of intralysosomal whorls and define a conserved pathway that couples nutrient sensing to membrane turnover and cellular aging.

cell biology↗

bioRxiv2025

Genome-wide screen identifies novel factors for surface protein cross-wall trafficking and cell envelope homeostasis in Staphylococcus aureus

Cell wall anchored surface proteins are integral components of the Gram-positive bacterial cell envelope and are vital for bacterial survival in different environmental niches. The trafficking of many surface proteins carrying a YSIRK/G-S signal peptide is synchronized with cell envelope biogenesis during cell division, whereby YSIRK proteins traffic to the septal membrane and anchor to septal peptidoglycan (cross-wall). Previous work demonstrated that LtaS-mediated lipoteichoic acid (LTA) synthesis restricts YSIRK proteins septal trafficking. Here we did a comprehensive immunofluorescence microscopy screen of the entire S. aureus Nebraska Transposon Mutant Library (NTML) for additional factors regulating cross-wall trafficking of staphylococcal protein A (SpA), an archetype of YSIRK proteins. We characterized the top nine major hits that drastically diminished SpA cross-wall localization, including ypfP and ltaA (LTA glycolipid anchor synthesis genes), lcpB (LytR-CpsA-Psr family protein), mprF (lysyl-phosphatidylglycerol synthase), lytH (cell wall hydrolase), scdA (nitrite reductase), yjbH (protease adaptor protein ), cbiO (cobalt transporter) and SAUSA300_2311 (LytTR regulatory system) along with {Delta}tagO (wall teichoic acid synthesis). Interestingly, unlike the ltaS mutant that delocalizes SpA at both the septal membrane and peptidoglycan (PG) layer, all the hits only delocalized SpA at the PG layer, suggesting that these mutants affect the late-stage SpA trafficking. In addition, mutants of lcpB, yjbH, cbiO and 2311 exhibit both transcriptional and spatial regulation. All the hits showed defects in cell cycle, cell morphology and spatially dysregulated PG synthesis. The shared phenotypes among the mutants suggest that impaired PG homeostasis and cell cycle defects are the mechanisms underlying dysregulated SpA localization. Overall, this work not only expands our understanding of YSIRK protein cross-wall trafficking but also identifies new leads that have a broader impact on the dynamics of cell cycle and cell envelope homeostasis. ImportanceSurface proteins of gram-positive bacteria are key virulence factors in human pathogen S. aureus. Most surface proteins carry a YSIRK/G-S type signal peptide that promotes cross-wall trafficking and attachment to septal cell wall during cell division. This study identified several new factors regulating this process through a comprehensive screen. The mutants identified here display dysregulated cell wall synthesis along with cell cycle defects. The results provide new insight into virulence factor trafficking and cell envelope homeostasis, which lays the foundation for development of new antimicrobial therapeutics.

microbiology↗

bioRxiv2025

DCBK: A Fragment-Based Hybrid Simulation and Machine Learning Framework for Predicting Ligand Dissociation Kinetics

Predicting small-molecule dissociation kinetics remains challenging due to the high computational cost of simulating rare unbinding events and the limited scalability of existing approaches. Here, we introduce DCBK (Divide-and-Compute Binding Kinetics), a physics-informed, fragment-resolved framework for predicting ligand dissociation across diverse protein-ligand systems. DCBK integrates steered molecular dynamics and umbrella sampling to reconstruct unbinding pathways and free energy profiles, followed by BRICS-based ligand fragmentation. Fragment-level energetic and structural features are combined with machine learning trained on experimental kinetics data, enabling efficient prediction of dissociation rate constant (koff) values. Validation across five protein families demonstrates strong agreement with experiments, with ablation and unseen-target analyses highlighting the contribution of fragment-level features and the frameworks transferability. Importantly, DCBK allows dissociation kinetics to be interpreted in terms of fragment-level contributions, offering mechanistic insight and guiding ligand modification to optimize residence time. This interpretable and extensible framework links molecular structure, energetics, and kinetics, providing actionable insights for lead optimization and rational drug design.

molecular biology↗

bioRxiv2025

Universal super-resolution for subcellular fluorescence imaging

Super-resolution fluorescence microscopy has emerged as an essential instrument for investigating subcellular structures and monitoring intracellular physiology. Despite rapid advances driven by deep learning, most existing approaches are modality specific and exhibit limited generalizability, restricting their practical applicability. Here we introduce universal super-resolution (UniSR), a framework that operates across microscopes and subcellular structures without optical modifications or prior sample knowledge. UniSR is initially pre-trained on simulated image pairs to establish mappings from low-to high-resolution features and subsequently fine-tuned with only one experimental image pair, reducing data demand and acquisition time. Across wide-field and point-scanning modalities, UniSR enhances resolution to match structured illumination, single-molecule localization, or stimulated emission depletion microscopy. Applied to diverse biological samples, it reveals nanoscale structures, dynamic processes, and organelle interactions with high spatiotemporal fidelity. UniSR provides a practical and broadly generalizable tool for super-resolution imaging in live-cell research.

bioinformatics↗

bioRxiv2025

Transplantation of active mitochondria condensed in liquid-liquid phase-separated hydrogels ameliorates myocardial ischemia-reperfusion injury

Mitochondrial dysfunction is a key driver of myocardial ischemia-reperfusion injury (MIRI), which exacerbates cardiac damage following the restoration of blood flow. Although single-phase hydrogel-based mitochondria transplantation therapy (MTT) holds promise for restoring cellular energy metabolism, its effectiveness is limited by extracellular calcium-induced mitochondrial degradation. In this study, we design a thermo-sensitive hydrogel utilizing liquid-liquid phase separation (LLPS), composed of gelatin and polyethylene glycol (PEG), to condense freshly isolated mitochondria. Compared to conventional single-phase hydrogels, the LLPS hydrogel significantly increases the sol-gel transition temperature above physiological levels, allowing it to remain injectable at body temperature while enabling rapid mitochondrial release following transplantation. More importantly, the LLPS structure enhances mitochondrial packing density and protects the activity of condensed mitochondria against calcium toxicity through spatial confinement and gelatin-mediated calcium chelation. In vitro, LLPS hydrogel-condensed mitochondria exhibit improved mitochondrial membrane potential and ATP production ability compared to those delivered via single-phase gelatin hydrogel. In vivo, mitochondria released from the LLPS hydrogel are effectively internalized by cardiomyocytes, resulting in improved cardiac function and reduced tissue damage after MIRI. These findings suggest that LLPS-based hydrogels offer a promising strategy to enhance MTT efficacy for MIRI and other mitochondria-related disorders.

bioengineering↗

bioRxiv2025

A Population-scale Single-cell Spatial Transcriptomic Atlas of the Human Cortex

The genetic and spatial determinants of cell type diversity in human cerebral cortices remain poorly defined. Here, we present a population-level single-cell spatial transcriptomic atlas of human cortices from 71 donors across the lifespan. We identified 906 layer-specific genes showing conserved and divergent laminar expression patterns between humans and other species. Spatial analysis revealed neuronal vulnerability and glial activation during aging, together with a decline in the proportion of superficial SST neurons and their interactions with other cells. Disease-associated genes exhibited high cell-type and layer-specific expression, implicating the pathogenic role of spatially specific gene expression. Spatial cis-eQTL analysis identified regulatory variants linked to genes related to diseases like Tourette syndrome. Cross-species comparison demonstrated glial expansion in the human cortex, accompanied by enhanced neuron-glia communication via the neuregulin signaling. Together, we provide a comprehensive single-cell atlas of the human cortex that is essential for understanding aging, evolution, and disease pathogenesis.

neuroscience↗

bioRxiv2025

Bioinformatic inference of the exercise-responsive control of p70 S6 kinase through RPS6KB1 expression

Previous research suggests that the absolute levels of p70 S6 kinase (p70S6K) are a key determinant of the rate of skeletal muscle protein synthesis (MPS). p70S6K levels are in part determined by the transcriptional control of the gene encoding p70S6K, RPS6KB1, but the molecular mechanisms governing its expression are poorly understood. The purpose of this study was to infer the molecular regulatory network governing RPS6KB1 expression. We applied a novel bioinformatic network inference algorithm called CARNIVAL (CAusal Reasoning pipeline for Network identification using Integer VALue programming) to infer the signaling network downstream of canonical exercise sensors controlling RPS6KB1-specific transcription factors (TFs) after acute aerobic (AE) or resistance exercise (RE). CARNIVAL integrates a prior knowledge network, TF and signaling pathway activities inferred from transcriptomic data, and perturbation targets to predict the network that best explains the data. The networks revealed intracellular sensors and hormone receptors controlling RPS6KB1-specific TFs. Both exercise types resulted in AMPK-mediated SNAI1 regulation, but HIF1A was distinctly controlled (AE: PHD1-3, FIH; RE: AMPK). AE controlled FOXA1 via insulin, TGF-{beta}, and myostatin signalling, while RE controlled CEBPA via MAP3Ks. Our study is the first to apply a comprehensive bioinformatic network inference algorithm to infer causal exercise-responsive signaling networks. The results of our analysis motivate experimentally testable hypotheses pertaining to the molecular control of RPS6KB1 transcription in human skeletal muscle in response to aerobic and resistance exercise.

bioinformatics↗

bioRxiv2025

Methane Cycling Microbes are Important Predictors of Methylmercury Accumulation in Rice Paddies

Microbial production of methylmercury from inorganic mercury in rice paddies poses health risks to consumers of this essential dietary staple. Although mercury-methylating communities are well characterized, the microbial guilds contributing to methylmercury accumulation in rice paddies remain unclear. Here, we collected paddy soils across a mercury concentration gradient throughout the rice growing season to identify microbial and environmental factors influencing methylmercury dynamics. We show that hgcA gene abundance, the key gene required for methylation, was not a significant predictor of methylmercury concentration in paddy soils. We also show that merB gene abundance correlated with methylmercury in mercury-polluted rhizosphere samples. Methane cycling genes were actively expressed, and their beta-diversity was significantly associated with methylmercury levels. Methanogen abundance correlated with higher methylmercury under elevated total mercury concentrations. Analysis of the methanotroph-associated mbnT gene, implicated in demethylation, revealed an unexpected positive correlation with methylmercury. Multiple regression and machine learning models converged on mercury bioavailability and methanogen/methanotroph abundances as key predictors of methylmercury, with methanogen-associated hgcA gene abundance and methanogen-methanotroph interactions highlighted under flooded, low-redox conditions. These findings suggest that methane-cycling microbes play key roles in methylmercury cycling dynamics and point to management strategies that could simultaneously mitigate mercury pollution and greenhouse gas emissions. ImportanceMethylmercury is a microbially-derived neurotoxin that accumulates in rice, which is a global food staple. Predicting mercurys fate in rice paddies is challenging because of the interplay between microbes responsible for methylmercury cycling and variables that control mercury availability. Our study coupled genomic and geochemical measurements with machine learning to identify the key predictors of methylmercury accumulation in paddy soils. We demonstrate that methanogen and methanotroph abundance, and mercury bioavailability, are major predictors of methylmercury variability in paddies. We show that considering interactions between methane cycling guilds improves our capacity to predict methylmercury accumulation in soils compared to approaches that rely solely on mercury cycling genes. This work can inform remediation strategies for mercury in rice paddies but also wetlands and permafrost where methane and mercury cycling are tightly coupled. Such strategies could provide a solution to simultaneously mitigate methylmercury exposure and reduce greenhouse gas emissions amid global environmental change.

microbiology↗

bioRxiv2025

NPS neurons receive extensive input from auditory brainstem nuclei

Neurons that produce NPS send output to brain regions implicated in circadian function and threat responses, but less is known about the afferent control of NPS neurons. In this study, we used a conventional retrograde tracer, cholera toxin beta subunit (CTb), to identify afferents to the rostral-lateral parabrachial region that contains the main concentration of NPS neurons. We then used Cre-dependent rabies retrograde tracing in Nps-2A-Cre mice to identify inputs specifically to NPS neurons. Nps-expressing neurons receive heavy input from auditory brainstem structures, including the inferior colliculus, nucleus of the lateral lemniscus, superior olivary complex, and cochlear nucleus. These findings suggest an unexpected role for auditory information in controlling the activity of NPS neurons.

neuroscience↗

bioRxiv2025

Intermediate tissue oxygen level is required to observe murine FLASH skin sparing

ObjectiveThis study evaluated the hypothesis that baseline tissue oxygen (pO2) would modulate FLASH toxicity sparing in murine skin, using a wide range of pO2 values, with ultra-high dose rate (UHDR) versus conventional dose rate (CDR) irradiation. ApproachMurine leg tissue pO2 was systematically varied and measured during irradiation from a FLASH Mobetron 9 MeV linac at 25 Gy, comparing UHDR ({approx}240 Gy/s) to CDR ({approx}0.16 Gy/s), for radiation induced skin toxicity outcomes. Baseline tissue pO2 was systematically modulated in 5 different treatment cohorts, using different ranges of inhaled gas (room air, 100% oxygen, or carbogen) and through varying limb vascular compression (partial or full). Radiolytic oxygen consumption, gO2 (mmHg/Gy), was quantified in vivo, and induced macroscopic skin toxicity was scored daily post treatment. Main ResultsFLASH skin sparing was observed at a fixed dose of 25 Gy in groups with partial leg clamping (pO2{approx}7{+/-}4mmHg), inhaled air (pO2{approx}12{+/-}6mmHg) and 100% oxygen (pO2{approx}16{+/-}4mmHg), while reduction in ulceration progression was significant only in the air inhalation group. No FLASH effect was observed under anoxic conditions, via complete blood flow occlusion (pO2{approx}0{+/-}1mmHg), or when modulated by inhaled carbogen (pO2{approx}21{+/-}7mmHg). In vivo measurements of radiolytic oxygen consumption, gO2, correlated to initial pO2 under UHDR conditions (pO2{approx}4-16mmHg), with ulceration predominantly occurring at pO2 values above 16mmHg. Inspired carbogen induced the highest pO2 at which point there was no FLASH sparing, for any dose groups between 25 to 15 Gy, despite having large changes in damage with dose. At the specific dose level of 25 Gy studied, the toxicity scores under anoxia for both UHDR and CDR were low (toxicity scores < 1) with no differences observed. SignificanceThese findings point to the fact that moderate and low tissue pO2 is associated with diminished oxygen-mediated damage at UHDR but not CDR, seen with inspired room air or 100% oxygen. Anoxic and hyperoxic murine skin are associated with minimal and maximal radiation damage respectively, but also exhibit no apparent FLASH toxicity sparing effect, with further investigation warranted into if the FLASH toxicity sparing effect persists at higher doses under anoxia.

cancer biology↗