Biology subjects

Cao, X.

Publications and source records attributed to Cao, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Effects of diffusion MRI spatial resolution on human brain short-range association fiber reconstruction and structural connectivity estimation

Short-range association fibers (SAFs) are critical for cortical communications but are often underestimated in conventional resolution diffusion magnetic resonance imaging (dMRI) since they locate within a [~]1.5mm thin layer of superficial white matter. With the emergence of high-resolution diffusion imaging techniques, this study timely evaluated the effects of image spatial resolution on SAF reconstruction using simulation data and multi-resolution (2, 1.5, and 0.96 mm iso.) empirical data acquired on the same 20 healthy subjects using the gSlider sequence and 20 widely used tractography approaches. Resolution effects were qualitatively assessed through model fitting and tractography results and quantitatively evaluated using global and regional short-range connectivity strength (SCS). It is found that lower resolution systematically reduces SCS across all methods in a spatially varying manner. Moreover, tractography methods exhibit significant differences in resolution sensitivity, with diffusion tensor imaging (DTI) based single-tissue single-fiber tractography showing greater vulnerability than constrained spherical deconvolution (CSD)-based multi-tissue multi-fiber tractography. Probabilistic tracking with anatomical constraints (ACT) and filtering (SIFT) improves robustness. Finally, up-sampling data to nominally higher resolution partially mitigates resolution-induced degradation and improves SAF reconstruction accuracy, particularly for DTI tractography. Based on these findings, higher resolution and multi-shell imaging is recommended if possible. For a given dataset, data up-sampling and DTI-based probabilistic tracking with ACT is recommended for single-shell low b-value data. CSD-based probabilistic tracking with ACT and SIFT is recommended for single-shell higher b-value data and multi-shell data. In summary, this study systematically and quantitatively evaluated resolution effects on SAF reconstruction and structural connectivity estimation and provided practical guidelines for more accurate mapping of SAFs. These advances hold promises to improve the characterization of healthy and diseased human brains in a wide range of neuroscientific and clinical applications.

neuroscience↗

bioRxiv2025

IL-32 drives inflammatory responses in IFN-γ primed human macrophages via a Myddosome-dependent pathway and is elevated in COVID-19

IFN-{gamma} is secreted by multiple lymphoid subsets in response to antigen stimulation and can reprogram and prime macrophages epigenetically and transcriptionally to increase responses to inflammatory stimuli such as LPS, IL-1{beta} or TNF-. IFN-{gamma}-driven M1-like inflammatory macrophage states are shared across human immune-mediated inflammatory diseases (IMIDs) and while IFN-{gamma} is nonredundant for defense to intracellular pathogens it is unclear if this is also the case in IMIDs. To identify additional secreted ligands which could prime and induce M1-like macrophages we screened >600 human proteins in human primary macrophages. Using complementary functional genomics approaches, we discovered that IL-32{beta} induced an M1-like inflammatory state in non-primed and IFN-{gamma}-primed macrophages. IL-32{beta} induced signaling, transcriptional, tolerance, cross-tolerance, and inflammatory responses in macrophages which were MyD88, IRAK1 and Myddosome-dependent. These responses to host IL-32{beta} were similar to yet distinct from, those induced by microbial LPS. IL-32 protein was elevated in serum from patients with severe COVID-19 and IL-32{beta} together with IFN-{gamma} were expressed by T cells and induced a macrophage transcriptional response which was shared by monocytes and macrophages in mild and severe COVID-19.

immunology↗

bioRxiv2025

TIP-seq: A Single-cell Multiomics Approach for Simultaneous Transcriptome and Intracellular Protein Profiling

Single-cell multiomics technologies have significantly advanced our understanding of cellular heterogeneity; however, the concurrent profiling of mRNA transcripts and target proteins continues to pose a substantial challenge. To bridge the gap between single-cell sequencing and proteomic methods, we developed an innovative single-cell multiomics methodology, termed TIP-seq, which facilitates the simultaneous profiling of the transcriptome and intracellular proteins without prior cell manipulation. In TIP-seq, microfluidic technology is leveraged to integrate oligonucleotide-labeled antibodies with hydrogel beads, allowing for the capture of mRNAs and proteins from individual cells within droplets, thereby enabling high-throughput and precise dual-omics data acquisition. When applied to lung cell lines and non-small cell lung cancer (NSCLC) tissues, TIP-seq analysis revealed notable cellular heterogeneity and molecular dynamics, emphasizing the distinct immune cell interactions within NSCLC tissues. Key immune checkpoint interactions in NSCLC, such as SPP1-CD44, NECTIN2-TIGIT, and NECTIN2-CTLA4, along with functional alterations in tumor-associated dendritic cells (DCs) and T cells, were identified via TIP-seq, underscoring their pivotal roles in mediating immune suppression within the tumor microenvironment. Collectively, TIP-seq represents a powerful methodology for identifying novel therapeutic targets and biomarkers, thereby holding significant potential for the advancement of precision medicine in the treatment of lung cancer and other complex diseases.

biochemistry↗

bioRxiv2025

ENPP1 inhibitor with ultralong drug-target residence time as an innate immune checkpoint blockade cancer therapy

Only one in five patients is estimated to respond to immune checkpoint inhibitors, which primarily target adaptive immunity. To date, no FDA-approved immunotherapies directly activate the innate anti-cancer immunity--an essential driver of lymphocyte recruitment and potentiator of responses to existing cancer immunotherapies. ENPP1, the dominant hydrolase that degrades extracellular cGAMP and suppresses downstream STING-mediated innate immune signaling, has emerged as a promising therapeutic target. However, existing ENPP1 inhibitors have been optimized for prolonged systemic residence time rather than effective target inhibition within tumors. Here, we report the characterization of STF-1623, a highly potent ENPP1 inhibitor with an exceptionally long tumor residence time despite rapid systemic clearance, enabled by its high ENPP1 binding affinity and slow dissociation rate. We show that membrane-bound ENPP1 on tumor cells, not the abundant soluble ENPP1 in serum, drives tumor progression. Consequently, STF-1623 unleashes anti-tumor immunity and synergizes with ionizing radiation, anti-PD-L1 and anti-PD-1, and a DNA damaging agent to produce robust anti-tumor and anti-metastatic effects across multiple syngeneic mouse tumor models, all without detectable toxicity. Conceptually, this work establishes that a noncovalent small molecule inhibitor of ENPP1 with ultralong drug-target engagement offers a safe and precise strategy to activate STING within tumors, fulfilling an unmet need of innate immunotherapies in cancer. One Sentence SummaryA small molecule blocks ENPP1, reviving immune attack on tumors and enhancing immune therapy with minimal side effects in preclinical cancer models.

cancer biology↗

bioRxiv2025

Parkinson's-Linked Synaptojanin 1 Loss in Dopamine Neurons Triggers Synaptic Degeneration and Striatal TH Interneuron Compensation

Presynaptic endocytic dysfunction is an early feature of Parkinson's disease (PD), but how dopamine circuits adapt to chronic synaptic failure remains unclear. In dopamine neuron-specific Synaptojanin 1 knockout mice, loss of this PD-linked endocytic protein causes terminal dystrophy and striatal dopamine deficiency, yet motor coordination is preserved. Chronic endocytic failure induces striatal dopamine-like neurons (DALNs) with circuit-dependent dopaminergic protein accumulation. DALNs do not arise through transcriptional reprogramming; instead, they acquire dopaminergic proteins from midbrain dopamine neurons through selective long-range transfer that favors soluble cargoes and can convey disease-associated proteins, including -synuclein and tau. Functionally, DALNs support local dopamine production, partially preserve motor performance and increase resistance to acute dopaminergic lesions. This adaptation is shared across PD-linked endocytic mutants and is developmentally constrained, but is not reproduced by acute denervation. Thus, synaptic endocytic stress triggers inter-neuronal protein transfer as an adaptive circuit mechanism supporting dopamine compensation and neuroprotection in early PD.

neuroscience↗

bioRxiv2025

A high-throughput platform for biophysical antibody developability assessment to enable AI/ML model training

Antibodies must bind their targets with high affinity and specificity to achieve useful therapeutic activity. They must also possess suitable developability properties (e.g., thermostability, solubility, viscosity, polyreactivity) to ensure favorable manufacturing, formulation, and in vivo performance. Both binding and developability properties are inherent to a given antibody amino acid sequence. Identification or selection of antibodies possessing suitable binding characteristics is now routine, and de novo computational design models, trained on extensive complementarity-determining region sequence and structural data, are rapidly improving. Developability properties, however, remain difficult to predict largely due to insufficient training data, with empirical testing being heavily used to avoid challenges in late-stage antibody development. To fill this gap, we built a high-throughput antibody developability assay platform designed to generate the large datasets needed to train improved machine learning (ML) models. We optimized and automated known developability assays [Jain et al., 2017], and developed a robust integrated data analytics pipeline. Here we report data on 246 antibodies--representing 106 approved, 135 clinical-stage, and 5 preregistration/withdrawn molecules--across a panel of 10 developability assays, in a "tidy data" format suitable for AI/ML modeling. We used these data to develop an XGBoost [Chen et al., 2016] ML model that better predicts similarity to approved antibodies compared to conventional use of developability warning thresholds. Additionally, we confirm that preliminary predictive models do improve with more training data. Our high-throughput PROPHET-Ab platform enables data generation at the scale needed to develop improved ML models to predict antibody developability. SignificanceSuccessful antibody drugs exhibit important "developability" properties, beyond tight and specific binding to their target, including high expressibility, high stability and solubility, low aggregation propensity, low viscosity, low polyreactivity, and long in vivo half-life. Collectively, developability properties predict favorable manufacturing, storage, administration, and safety, and deficiencies in these properties increase risk for clinical failure. Despite progress in developing machine learning models to predict structure and binding, antibody developability models lag, largely due to a lack of sufficiently large training datasets. We have built a high-throughput platform, PROPHET-Ab, that enables data generation at the scale needed to train improved AI/ML models to predict antibody developability.

biophysics↗

bioRxiv2025

Quantifying virus load and characterising virus diversity in wildlife samples with target enrichment sequencing

Metagenomics is a powerful tool for characterising viruses, with broad applications across diverse disciplines, from understanding the ecology and evolutionary history of viruses to identifying causative agents of emerging outbreaks with unknown aetiology. Additionally, metagenomic data contains valuable information about the amount of virus present within samples. However, we have yet to leverage metagenomics to assess viral load, which is a key epidemiological parameter. To effectively use sequencing outputs to inform transmission, we need to understand the relationship between read depth and viral load across a diverse set of viruses. Here, using target enrichment sequencing, we investigated the detection and recovery of virus genomes by spiking known concentrations of DNA and RNA viruses into wild rodent faecal samples. In total, 15 experimental replicates were sequenced with target enrichment sequencing and compared to shotgun sequencing of the same background samples. Target enriched sequencing recovered all spike-in viruses at every concentration (102, 103, and 105 {+/-} 1 log genome copies) and showed a log-linear relationship between spike-in concentration and mean read depth. Background viruses (including Kobuvirus and Cardiovirus) were recovered consistently across all biological and technical replicates, but genome coverage was variable between virus genera and likely reflected the composition of target enrichment probe panel. Overall, our study highlights the strengths and weaknesses of using commercially available panels to quantify and characterise wildlife viromes, and underscores the importance of probe panel design for accurately interpreting coverage and read depth. To advance the use of metagenomics for understanding virus transmission, further research will be needed to elucidate how sequencing strategy (e.g. library depth, pooling), virome composition, and probe design influence viral read counts and genome coverage.

genomics↗

bioRxiv2025

Genetic and functional analysis of unproductive splicing using LeafCutter2

Alternative splicing commonly generates unproductive mRNA transcripts that harbor premature termination codons1, leading to their degradation by nonsense-mediated decay (NMD). These events reduce overall protein expression levels of affected genes, potentially contributing to gene regulation and disease mechanisms. Here, we present LeafCutter2, which enables identification and quantification of unproductive splicing from short-read RNA-seq data. LeafCutter2 requires minimal gene annotations (start and stop codons) to annotate NMD-inducing splicing events, and identifies differential unproductive splicing between groups, providing insights into its contributions to differential gene expression. Moreover, LeafCutter2 enables mapping of unproductive splicing quantitative trait loci (u-sQTLs), which often colocalize with expression QTLs and GWAS loci. Applying LeafCutter2 to RNA-seq data across human and 6 non-human species, we uncovered a broad landscape of unproductive splicing, which varies widely across tissues. Strikingly, we observed a conserved developmental-stage-specific increase in unproductive splicing during testis maturation across all species. In Alzheimers disease (AD), we analyzed RNA-seq data from the AD Functional Genomics consortium FunGen-xQTL project and identified unproductive splicing events in 18 AD risk genes, including TSPAN14, PICALM, and CASS4, likely mediating genetic effects on disease risk. We performed an integrative analysis using gene expression QTLs, protein expression QTLs, and AD GWAS data, showing that unproductive splicing provides unique regulatory insights beyond traditional approaches. Thus, LeafCutter2 represents a powerful tool for understanding the functional impact of alternative splicing on gene expression and disease mechanisms.

genomics↗

bioRxiv2025

A Phenotype-Driven Multi-Omic Atlas of Glioblastoma Invasion

BackgroundGlioblastoma (GBM) invasion is clinically decisive but difficult to model systematically. Existing patient-derived xenograft (PDX) resources rarely couple reproducible in vivo invasion phenotypes with matched multi-omic profiles at scale, limiting mechanistic insight and phenotype-informed therapeutic hypotheses. MethodsWe established the HGCC Phenobank, comprising 65 patient-derived GBM stem-like cultures with matched multi-omic profiling and orthotopic engraftment in 449 mice. Blinded histopathology quantified ten invasion traits per case. These phenotypes were integrated with RNA sequencing, DNA methylation, and mass-spectrometry-based proteomics. Multi-Omic Factor Analysis (MOFA) identified latent molecular programs. Phenotype-specific RNA signatures were matched to LINCS drug-perturbation profiles and validated in 3D gliomasphere and ex vivo brain-slice assays. ResultsTwo dominant, reproducible invasion modes emerged across models: diffuse parenchymal infiltration and perivascular/condensed growth. Proneural cultures formed more aggressive tumors in immunodeficient mice, and mouse survival showed a modest correlation with patient survival in matched cases (Pearson r = 0.1832, p = 0.045). MOFA identified 15 latent factors; Factor 1, enriched for ASCL1/OLIG1/OLIG2 programs and associated with TP53/DCHS2/WNK2 alterations, was linked to increased tumor formation, diffuse invasion, and shorter mouse survival, and stratified GBM patients in TCGA and in our matched patient cohort. Drug-signature matching separated mechanisms targeting diffuse versus perivascular invasion. Experimental validation confirmed phenotype-selective sensitivities, and inhibitors PIK-75 and buparlisib suppressed invasion dynamics across representative models in 3D and brain-slice assays. ConclusionsThe HGCC Phenobank provides the first openly available PDX resource that systematically links GBM invasion phenotypes to multi-omic programs and therapeutic predictions. This framework enables reproducible model selection, mechanistic dissection of invasion modes, and phenotype-guided therapeutic discovery. Key PointsO_LIDiffuse and perivascular invasion define orthogonal GBM axes C_LIO_LIASCL1/OLIG factor links initiation, diffuse growth, and survival C_LIO_LIPhenotype-matched drugs validated; PIK-75 and buparlisib curb invasion dynamics C_LI Importance of the StudyGlioblastoma invasion varies substantially between patients, yet existing patient-derived xeno-graft resources rarely combine reproducible in vivo phenotyping with matched multi-omic profiling at scale. The HGCC Phenobank addresses this gap with standardized, blinded scoring of ten invasion traits across 449 orthotopic xenografts from 65 molecularly characterized GBM stem-like cultures, integrated with transcriptomic, methylomic, and proteomic data. We identify two dominant, reproducible invasion modes and a cross-modal neurodevelopmental program, the ASCL1/OLIG1/2-associated Factor 1, that links tumor initiation, diffuse growth, and survival in mice, and stratifies GBM patients in TCGA and in our matched patient cohort. In a spatially resolved xenograft section, Factor 1 signal localizes to the invasive tumor periphery. By matching phenotype-specific RNA signatures to drug-induced transcriptional responses, we show that invasion phenotypes nominate selective vulnerabilities, exemplified by PIK-75. This openly shared resource enables reproducible model selection, mechanistic dissection of invasion programs, and phenotype-guided therapeutic discovery.

cancer biology↗

bioRxiv2025

The TONSL-MMS22L complex and FANCM form an interdependent complex on chromatin to counter replication stress

FANCM is branchpoint DNA translocase essential for cellular response to replication stress. Here, we show that replication stress stimulates FANCM and the TONSL-MMS22L heterodimer bound to histones H3-H4 to form an interdependent complex on chromatin. TONSL-MMS22L recruits FANCM and Fanconi anemia (FA) core complex to stalled and collapsed forks, maintains FANCM on replication-stressed chromatin, promotes FANCD2 monoubiquitination, facilitates both repair and replication traverse of DNA interstrand crosslinks (ICLs), and suppresses sister chromatid exchanges, through its interactions with FANCM and H3-H4. Reciprocally, both DNA translocase activity and phosphorylation of FANCM facilitate recruitment of TONSL-MMS22L and RAD51 to perturbed forks. Moreover, TONSL-MMS22L and FANCM function together to promote activation of the FA pathway, ICL repair, homologous recombination and replication traverse. Cancer patients with tumors with wildtype FANCM and low expression of TONSL-MMS22L have a more favorable prognosis than those with high expression. Thus, FANCM-TONSL-MMS22L acts coordinately as a complex on chromatin that resolves replication stress, and this complex may present a therapeutic target for wildtype FANCM-linked cancer.

cell biology↗

bioRxiv2025

MYB93 regulates responses to environmental sulphur in Arabidopsis and tomato.

Sulphur (S) is an important nutrient that has wide-ranging effects on plant health and metabolism. Several classes of transcription factor respond to S deprivation, including R2R3-MYBs. In Arabidopsis, the AtMYB93 transcription factor-encoding gene is upregulated by S deprivation. AtMYB93 has a non-redundant function in lateral root development and redundant functions in suberin biosynthesis alongside related MYB transcription factors, but AtMYB93s role in S signalling, and how it relates to lateral root development, is unknown. We show that the transcriptome of Atmyb93 mutant roots implicates AtMYB93 in responses to S, including changes in S transport and metabolism, and flavonoid- and carbohydrate metabolism. Elemental analysis demonstrates that the Atmyb93 mutant has elevated shoot S levels while tomato SlMYB93-overexpressing plants have reduced shoot S. We uncover a stimulatory effect of S deprivation on adventitious root development. However, Atmyb93 mutants do not show significant changes in sensitivity to S with respect to lateral-or adventitious root development, most likely due to some functional redundancy. Moreover, AtMYB93 promoter activity is not spatially regulated by S deprivation. Taken together, our data suggest that AtMYB93 has a role in mediating root responses to S in alongside other root transcription factors.

plant biology↗

bioRxiv2025

DMC-BrainMap - an open-source, end-to-end tool for multi-feature brain mapping across species

A central goal of current neuroscience research is to understand how behavior emerges from neuronal circuit activity. For this, cellular and circuit components in intact brains need to be identified and studied using e.g. viral tracing, electrophysiology, imaging, activity perturbations, and behavior. A commonality of these approaches is the need to establish the anatomical locations of both experimental parameters (e.g. recording/injection sites) and circuit components (e.g. cell bodies/projections). The development of standardized coordinate systems, i.e. reference brain atlases, has proven essential for reproducible, cross-laboratory mapping of anatomical data. However, the process of mapping, analyzing, and visualizing anatomical data remains challenging, especially for users lacking programming expertise. Here, we introduce DMC-BrainMap, an open-source napari plugin designed as a user-friendly tool for streamlined processing and whole-brain analysis of anatomical data. The working principle and core functionalities include all steps after image acquisition, i.e., preprocessing of images, registration of images to a reference atlas, segmentation of different anatomical features, and data analysis/visualization. DMC-BrainMap can be applied to histological data obtained from a variety of model organisms at different developmental stages, including mouse, rat, and zebrafish. We demonstrate the utility of DMC-BrainMap by mapping and quantifying cell bodies, axonal densities, injection sites as well as placement of optical fibers and Neuropixels probes. Further, we show how spatial transcriptomics data can be integrated into the DMC-BrainMap workflow. By eliminating the need for programming by the user, DMC-BrainMap provides an easy-to-use tool for increased rigor, reproducibility, and data sharing in neuroscientific research involving animal models.

neuroscience↗

bioRxiv2025

China Autism Brain Imaging Consortium: Charting Brain Growth in Chinese Children with Autism

Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition characterized by atypical brain growth. While advances in neuroimaging and openly sharing large-sample datasets such as the Autism Brain Imaging Data Exchange (ABIDE) have improved understanding of ASD, most studies focus on adolescents and adults, with early brain development-critical for diagnosis and intervention-remaining underexplored. Existing research predominantly involves Western samples, offering limited insight and generalizability into non-Caucasian populations. We introduce the China Autism Brain Imaging Consortium (CABIC) (https://php.bdnilab.com/resources/), a grassroots effort by researchers across the country to aggregate previously collected multi-site structural MRI datasets and phenotypic information from 1,451 autistic children and 1,119 typically developing children, covering an age range from early childhood to school age (1.0 - 12.92 years). Here, we present this resource and depict brain growth charts to push forward a more comprehensive understanding of the brain development in Chinese autism children. We constructed brain growth charts that reveal a developmental shift in autistic children, transitioning from early overgrowth to delayed maturation. Regional analyses identified distinct atypical trajectories across specific brain regions. Individual deviation scores quantified inter-subject variability, characterizing the heterogeneity of brain development in ASD. Comparative analyses between CABIC and ABIDE highlighted differences potentially attributable to ethnicity and culture, advancing our understanding of cross-population neurodevelopmental diversity. CABIC MRI datasets will be shared publicly to foster investigation of the potential neural mechanisms underlying ASD in non-Western populations and support efforts toward precision medicine for autistic individuals across diverse backgrounds.

neuroscience↗

bioRxiv2025

Myocardial cGMP-PKG1alpha dysregulation contributes to VT pathogenesis in type II diabetes and metabolic syndrome.

BackgroundType-II diabetes (DMII) and metabolic syndrome increase ventricular arrhythmia and sudden cardiac death risk. ObjectivesTo identify signaling mechanisms through which DMII and metabolic syndrome promote ventricular tachycardia (VT). MethodsWe performed ventricular programmed stimulation on leptin receptor mutant (Db/Db) mice with DMII, high fat high sucrose (HFHS)-fed mice with metabolic syndrome, and cGMP-dependent Protein Kinase 1 (PKG1) leucine zipper mutant (LZM) mice, which do not have DMII or metabolic syndrome but have disrupted PKG1 signaling. ResultsDuring ventricular programmed stimulation, Db/Db and HFHS-fed mice displayed increased VT and T-wave alternans. Cardiomyocytes from these mice displayed early afterdepolarizations. Both models demonstrated decreased heart rate response to parasympathetic inhibition, indicating autonomic dysfunction. cGMP, which mediates cardiac parasympathetic stimulation, was reduced in LVs of Db/Db and HFHS-fed mice. Conversely, cGMP augmentation with soluble guanylate cyclase stimulation (riociguat) or phosphodiesterase 5 inhibition (sildenafil) reduced VT inducibility. PKG1 LZM mice had normal autonomic responsiveness, but excess VT inducibility. Db/Db, HFHS, and LZM mice each demonstrated hyperactivated myocardial glycogen synthase kinase3{beta} (GSK3{beta}). Further, GSK3{beta} inhibition with TWS119 abolished inducible VT in these mice. Diastolic cytosolic Ca2+ reuptake slope decreased in cardiomyocytes from all models, while GSK3{beta} inhibition with TWS119 reversed this effect. Phospholamban (PLB), which inhibits sarcoplasmic/endoplasmic reticulum Ca2+ ATPase 2a-mediated Ca2+ reuptake, was hyperactivated/hypophosphorylated in HFHS-fed and LZM mice, and this was reversed by TWS119. ConclusionsThese findings identify cGMP reduction as driving GSK3{beta} hyperstimulation, calcium dyshomeostasis, and VT in DMII and metabolic syndrome. Pharmacological modulation of these pathways opposes VT pathogenesis.

molecular biology↗

bioRxiv2025

Inhibition of SQSTM1/p62 oligomerization and Keap1 sequestration by the Cullin-3 adaptor SHKBP1

SQSTM1/p62 is a master regulator of the autophagic and ubiquitination pathways of protein degradation and the antioxidant response. p62 functions in these pathways via reversible assembly and sequestration of additional factors into cytoplasmic phase-separated structures termed p62 bodies. The physiological roles of p62 in these various pathways depends on numerous mechanisms for regulating p62 body formation and dynamics that are incompletely understood. Here, we identify a new mechanism for regulation of p62 oligomerization and incorporation into p62 bodies by SHKBP1, a Cullin-3 E3 ubiquitin ligase adaptor, that is independent of its potential functions in ubiquitination. We map a SHKBP1-p62 protein-protein interaction outside of p62 bodies that limits p62 assembly into p62 bodies and affects the antioxidant response by preventing sequestration and degradation of Keap1. These studies provide a non-ubiquitination-based mechanism for an E3 ligase adaptor in regulating p62 phase separation and cellular responses to oxidative stress.

cell biology↗

bioRxiv2025

Fusobacteria nucleatum determines the expression of amphetamine-induced behavioral responses through an epigenetic phenomenon.

Amphetamines (AMPHs) are psychostimulants commonly used for the treatment of neuropsychiatric disorders. They are also misused (AMPH use disorder; AUD), with devastating outcomes. Recent studies have implicated dysbiosis in the pathogenesis of AUD. However, the mechanistic roles of microbes in AUD are unknown. Fusobacterium nucleatum (Fn) is a bacterium that increases in abundance in both rats and humans upon AMPH exposure. Fn releases short-chain fatty acids (SCFAs), bacterial byproducts thought to play a fundamental role in the gut-brain axis as well as the pathogenesis of AUD. We demonstrate that in gnotobiotic Drosophila melanogaster, colonization with Fn or dietary supplementation of the SCFA butyrate, a potent inhibitor of histone deacetylases (HDACs), enhances the psychomotor and rewarding properties of AMPH as well as its ability to promote male sexual motivation. Furthermore, solely HDAC1 RNAi targeted inhibition recapitulates these enhancements, pointing to a specific process underlying this Fn phenomenon. Of note is that the expression of these AMPH behaviors is determined by the increase in extracellular dopamine (DA) levels that result from AMPH-induced reversal of DA transporter (DAT) function, termed non-vesicular DA release (NVDR). The magnitude of AMPH-induced NVDR is dictated, at least in part, by DAT expression levels. Consistent with our behavioral data, we show that Fn, butyrate, and HDAC1 inhibition enhance NVDR by elevating DAT expression. Thus, the participation of Fn in AUD stems from its ability to release butyrate and inhibit HDAC1. These data offer a microbial target and probiotic interventions for AUD treatment.

neuroscience↗

bioRxiv2025

LCORL and STC2 variants increase body size and growth rate in cattle and other animals

Using ancestral recombination graphs, we investigated recent selection signatures in European beef cattle breeds, pinpointing sweep-driving variants in the LCORL and STC2 loci with notable effects on body size and growth rate. The ACT-to-A frameshift mutation in LCORL occurs mainly in central-European cattle, and stimulates growth. Remarkably, convergent truncating mutations were also found in commercial breeds of sheep, goats, pigs, horses, dogs, rabbits, and chickens. In the STC2 gene, we identified a missense mutation (A60P) located within the conserved region across vertebrates. We validated the two natural mutations in gene-edited mouse models, where both variants in homozygous carriers increase the average weight by 11%. Our findings provide insights into a seemingly recurring gene target of body size enhancing truncating mutations across domesticated species, and offer valuable targets for gene editing-based breeding in animals.

genetics↗

bioRxiv2024

Single-cell RNA sequencing analysis reveals new insights for intersex gonad initiation and early sex differentiation of goats

Polled intersex syndrome in goats severely impacts productivity and economic benefits, serving as a potential model for human reproductive defects. However, its specific molecular and cellular regulatory mechanisms remain unclear. This study combined single-cell RNA-sequencing (scRNA-seq) with tissue morphology and immunofluorescence detection to investigate the cellular heterogeneity, pseudo-time differentiation trajectory, differentially expressed genes, and regulatory networks of female, intersex, and male gonads during the 55-65 days embryonic stage of goats. The results indicated significant heterogeneity and cell fate transition in the somatic and germ cells of female, intersex, and male gonads at different developmental stages. Stromal cells may initiate female and intersexual gonad development, and epithelial cells may be the source of gonad cells in male fetuses. The abnormal expression of FOXL2, SOX9, AMH, DMRT1, RSPO1, INSL3, TCF21 and CSF1R may cause female-to-male sex reversal. The new candidate genes like PHLDB2, ZNRF3 and TEAD1 may contribute to the gender differentiation. Additionally, TREM2+ macrophages analogous to those in humans were identified in male gonads, while genes such as CSF1R and TYROBP potentially regulate macrophage immune privilege mechanisms. Early gonadal development in goats may also be regulated by circadian rhythm mechanisms similar to humans, with genes such as NR1D1, LGR4, and ATG5 involved in granulosa cell development, while genes such as ATG5, NRIP1, and FBXW11 may affect intersex trait development. In general, this study provided an important reference for exploring molecular and cellular mechanisms of intersex initiation during early embryonic development in goats and also for modelling human reproductive defects. Author summaryIn this study, we investigated the cell fate trajectory and key gene expression profile of goat fetus gonads using scRNA-seq. The analysis revealed cellular heterogeneity among normal male, normal female, and intersex gonadal somatic and germ cells, alongside their dynamic fate transitions across various developmental states. Pseudo-time trajectory analysis suggested that stromal cells might act as the initiation signal for female and intersexual gonad development, while epithelial cells could serve as the primary source of gonadal cells in male fetal goats. GO functional enrichment and KEGG analyses confirmed that abnormal expression of FOXL2, SOX9, AMH, DMRT1 and RSPO1 was linked to the emergence of intersexual gonads. Newly identified candidate genes including LRP2, PITX2, ARX, LHX9, PHLDB2, ZNRF3 and TEAD1 may contribute to sex-specific differences, while INSL3 and TCF21 could be linked to intersexual gonads. We identified TREM2+ macrophages analogous to those in humans, which could regulate immune privilege mechanisms. Circadian rhythmic changes were observed during early goat gonadal development.

developmental biology↗