Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 415 records · Page 23Linked to original sources

bioRxiv2024

Elevational constraints on flight efficiency shape global gradients in avian wing morphology

Wings with elongated shape or larger surface area are associated with increased flight efficiency and dispersal ability in a wide range of animals from insects to birds 1-4. Inter- and intraspecific variation in these attributes of wing shape is determined by a range of factors - including foraging ecology, migration and climatic seasonality 5-8 - all of which may drive latitudinal gradients in wing morphology 9,10. A separate hypothesis predicts that wing shape should also follow an elevational gradient because air density and oxygen supply decline with altitude 11, altering the aerodynamics of flight, and driving the evolution of more efficient wings in high-elevation species to compensate for reduced lift 12,13. However, previous analyses have found only mixed support for the thin-air hypothesis 14-18, and we currently lack a global synthesis of elevational gradients in wing design for any taxonomic group. In this study, we use phylogenetic comparative models to explore elevational effects on wing morphology in 9986 bird species, while accounting for multiple climatic and ecological attributes, including latitude, temperature seasonality, body mass, aerial lifestyle and migration. We found that relative wing elongation (hand-wing index) and wing area increase with elevation, particularly in the upper montane zone (>4 km above sea level). These results confirm a pervasive elevational gradient in avian wing morphology, highlighting the role of aerodynamic constraints as key mechanisms shaping global patterns of trait evolution in flying animals.

evolutionary biology↗

bioRxiv2024

Single-cell resolved differentiation of pre-Kranz anatomy in maize leaf primordia

Typical C4 plants such as maize possess highly optimized Kranz-type leaf anatomy, whereby concentric wreaths of mesophyll and bundle sheath cells surround closely spaced veins. The veins and the cells that surround them are derived from the middle ground meristem (mGM) through processes that are as yet undefined. Here we distinguished the active zone of vascular development within early leaf primordia, and used comparative transcriptomics of sub-sectioned maize and rice primordia to identify cohorts of genes likely involved in early Kranz development. Leveraging single-nucleus RNA sequencing (snRNA-seq) we then explored the cell heterogeneity and developmental trajectories within single maize leaf primordia. Assisted by in situ hybridization, cell clusters of mGM and procambium were identified, with candidate marker genes showing different yet inter-related expression patterns. Localization of the vascular marker ZmSHR1 was preceded by that of ZmEREB161 and ZmEREB114 in terms of procambium initiation. Potential subclusters of bundle sheath cells and different layer of mesophyll cells were depicted from developing cells toward the tip of sub-sectioned maize primordia. Collectively our results identify potential mGM derived or procambium localized Kranz regulators and provide resources for investigating leaf vein development in maize and rice, at sub-primordium and single-cell resolution.

plant biology↗

bioRxiv2024

A systematic evaluation of dynamic functional connectivity methods using simulation data

Numerous dynamic functional connectivity (dFC) methods have been proposed to study time-resolved network reorganization in rest and task fMRI. However, a comprehensive comparison of their performance is lacking. In this study, we compared the efficacy of seven dFC methods (and their enhanced versions) to track transient network reconfiguration using simulation data. The seven methods include flexible least squares (FLS), dynamic conditional correlation (DCC), general linear Kalman filter (GLKF), multiplication of temporal derivatives (MTD), sliding-window functional connectivity with L1-regularization (SWFC), hidden Markov models (HMM), and hidden semi-Markov models (HSMM). Multiple datasets of non-fMRI-BOLD and fMRI-BOLD signals with predefined covariance structures, signal-to-noise ratio levels, and sojourn time distributions were simulated. We adopted inter-subject analysis to eliminate the effects of signals of non-interest, resulting in enhanced methods: ISSWFC, ISMTD, ISDCC, ISFLS, ISKF, ISHMM, and ISHSMM. Efficacy was defined as the spatiotemporal association between simulated and estimated data. We found that all enhanced dFC methods outperformed their original versions. Efficacies depend on several factors, such as considering the neurovascular effect in simulated data, the covariance structure between two time series, state sojourn distribution, and signal-to-noise ratio levels. These results highlight the importance of selecting appropriate dFC methods in fMRI study.

neuroscience↗

bioRxiv2024

Dihydromyricetin alleviated the damage of hypoxia-induced mouse neurons by reducing ROS levels and inhibiting the expression of PAR and gammaH2AX

ObjectiveTo investigate the effect of dihydromyricetin on hypoxia-induced neurons, to understand the effect of dihydromyricetin on hypoxic-ischemic encephalopathy (HIE). MethodsCortical neurons were isolated from C57BL/6j mice (24 hour-year old), cultured, and subjected to 4h hypoxia and 20h reoxygenation to mimic the neonatal hypoxic-ischemic encephalopathy. After dihydromyricetin (20mol/L) treatment of hypoxia-induced neurons for 2h, CCK-8 assay was used to analyze the neuronal viability, Hoechst33342/PI double staining assay was used to analyze the neuronal death, Western blotting was used to analyze the expression of Poly ADP-ribose (PAR) polymer protein and {gamma}H2AX, comet assay was used to detect DNA damage, immunofluorescence staining was used to observe the nuclear translocation of apoptosis inducing factor, and 2,7-dichlorodihydrofluorescein diacetate was used to detect the expression of reactive oxygen species (ROS). ResultsCompared with the control groups, hypoxia-treated neurons exhibited significantly lower activity, higher neuronal death rate and the high expressions of PAR and {gamma}H2AX, hypoxia could also induce AIF nuclear translocation, increase tail DNA content and tail length, increase the expression of ROS in neurons; after dihydromyricetin treatment, neuronal activity were significantly increased, neuronal death rate, ROS levels, and the expressions of PAR and {gamma}H2AX were also decreased, AIF nuclear translocation was inhibited, the tail DNA content and tail length were also decreased. ConclusionDihydromyricetin could alleviate the damage of hypoxia-induced neurons through decreasing the levels of ROS and inhibiting the expressions of PAR and {gamma}H2AX, suggesting that dihydromyricetin may have the protective effect on HIE.

neuroscience↗

bioRxiv2024

The Haemagglutinin Genes of the UK Clade 2.3.4.4b H5N1 Avian Influenza Viruses from 2020 to 2022 Retain Strong Avian Phenotype

Since 2020, the United Kingdom (UK) has suffered repeated epizootics of clade 2.3.4.4b H5 high pathogenicity avian influenza viruses (HPAIVs) in wild birds and poultry, resulting in substantial economic losses due to enforced statutory control. The rapid evolution of H5 HPAIVs continues to raise concern with heightened zoonotic and pandemic risks. The immunodominant haemagglutinin glycoprotein (HA) is crucial for influenza virus receptor binding and pH-induced fusion of viral and cellular membranes. Mutations in HA are frequent due to polymerase error, immune pressure and host adaptation, resulting in antigenic modulation and/or an expansion of host tropism, respectively, ultimately hindering control strategies. We evaluated a comprehensive panel of H5 viruses representing prevalent genotypes from UK outbreaks spanning 2020 to 2022 for HA functionality. HA genes from each genotype were assessed through receptor binding, pH of fusion, thermostability and HA inhibition assays to evaluate factors contributing to zoonotic potential, stability, and antigenicity. The viruses only bound to avian receptors and exhibited fusion at a pH of 5.8, above the pH range (pH 5.0 to 5.5) associated with efficient human-to-human transmission. Therefore, these H5 viruses have low immediate zoonotic threat. Contemporary H5 viruses were more thermostable and showed antigenic drift compared to the earlier 2017-2018 clade 2.3.4.4b H5N8 viruses, and N236D in HA was identified as a significant antigenic epitope. The findings of this study underscore the evolving nature of the HA of these viruses and highlight the importance of ongoing surveillance and characterisation efforts to identify factors that might contribute to zoonotic risk.

microbiology↗

bioRxiv2024

Ultra-resolution Deconvolution of Spatial Transcriptomics Unveils Spatiotemporal Cellular Dynamics in Complex Microenvironments

Immune cells infiltrate tissues in response to exogenous pathogens or spontaneous tumors, generating protective immunity to safeguard tissues. Despite advancements in spatial transcriptomics (ST), the precise spatial distribution and functional specialization of immune cells within tissue microenvironments remain elusive. Here, we introduce an ultra-precision ST deconvolution algorithm (UCASpatial) that enhances the mapping of cell subpopulations to spatial locations by leveraging the contribution of genes indicative of cell identity through entropy-based weighting. Using both in silico and real ST datasets, we demonstrate that UCASpatial improves the robustness and accuracy in identifying low-abundant cell subpopulations and distinguishing transcriptionally heterogeneous cell subpopulations. Applying UCASpatial to human colorectal cancer (CRC), we link genomic alterations in individual cancer clones to multi-cellular characteristics of the tumor immune microenvironment (TIME) and reveal the co-evolution of tumor cells and TIME at a clonal resolution. We show that the copy number gain on chromosome 20q (chr20q-gain) in tumor cells orchestrates a T cell-excluded TIME, indicative of resistance to immunotherapy in CRC, and is associated with tumor-intrinsic human endogenous retrovirus subfamily H (HERV-H) silencing and impaired type I interferon response. In murine wound healing models, we illuminate the spatiotemporal dynamics of individual cell subsets across various stages of the healing process. We discovered that the scarring-healing mice (C57BL/6) exhibited a replacement of Prg4+ chondrogenic progenitors to Igfbp5+ chondrocytes in the wound bed at the regeneration stage, a change not observed in the regenerative strain (MRL/MpJ). The Igfbp5+ chondrocyte, spatially coordinating with Cd36+ Gpnmb+ Il1b- macrophage and Fmod+ fibroblast, forms a pro-fibrotic community associated with regeneration failure. The cell-cell interactions within this three-cell cluster, mediated by the IL11-IL11RA axis, drive the pro-fibrotic community formation and limit regeneration in C57BL/6 mice. Our findings present UCASpatial as a versatile tool for deciphering fine-grained cellular landscapes in ST and exploring intercellular mechanisms in complex and dynamic microenvironments.

bioinformatics↗

bioRxiv2024

Disruption of the PGE2 synthesis / response pathway restrains atherogenesis in programmed cell death-1 (Pd-1) deficient hyperlipidemic mice

Immune checkpoint inhibitors (ICIs) that target programmed cell death 1 (PD-1) have revolutionized cancer treatment by enabling the restoration of suppressed T-cell cytotoxic responses. However, resistance to single-agent ICIs limits their clinical utility. Combinatorial strategies enhance their antitumor effects, but may also enhance the risk of immune related adverse effects of ICIs. Prostaglandin (PG) E2, formed by the sequential action of the cyclooxygenase (COX) and microsomal PGE synthase (mPGES-1) enzymes, acting via its E prostanoid (EP) receptors, EPr2 and EPr4, promotes lymphocyte exhaustion, revealing an additional target for ICIs. Thus, COX inhibitors and EPr4 antagonists are currently being combined with ICIs potentially to enhance antitumor efficacy in clinical trials. However, given the cardiovascular (CV) toxicity of COX inhibitors, such combinations may increase the risk particularly of CV AEs. Here, we compared the impact of distinct approaches to disruption of the PGE2 synthesis /response pathway - global or myeloid cell specific depletion of mPges-1 or global depletion of Epr4 - on the accelerated atherogenesis in Pd-1 deficient hyperlipidemic (Ldlr-/-) mice. All strategies restrained the atherogenesis. While depletion of mPGES-1 suppresses PGE2 biosynthesis, reflected by its major urinary metabolite, PGE2 biosynthesis was increased in mice lacking EPr4, consistent with enhanced expression of aortic Cox-1 and mPges-1. Deletions of mPges-1 and Epr4 differed in their effects on immune cell populations in atherosclerotic plaques; the former reduced neutrophil infiltration, while the latter restrained macrophages and increased the infiltration of T-cells. Consistent with these findings, chemotaxis by bone-marrow derived macrophages from Epr4-/- mice was impaired. Epr4 depletion also resulted in extramedullary lymphoid hematopoiesis and inhibition of lipoprotein lipase activity (LPL) with coincident spelenomegaly, leukocytosis and dyslipidemia. Targeting either mPGES-1 or EPr4 may restrain lymphocyte exhaustion while mitigating CV irAEs consequent to PD-1 blockade.

pharmacology and toxicology↗

bioRxiv2024

A Message Passing Framework for Precise Cell State Identification with scClassify2

In single-cell analysis, the ability to accurately annotate cells is crucial for downstream exploration. To date, a wide range of approaches have been developed for cell annotation, spanning from classic statistical models to the latest large language models. However, most of the current methods focus on annotating distinct cell types and overlook the identification of sequential cell populations such as transitioning cells. Here, we propose a message-passing-neural-network-based cell annotation method, scClassify2, to specifically focus on adjacent cell state identification. By incorporating prior biological knowledge through a novel dual-layer architecture and employing ordinal regression and conditional training to differentiate adjacent cell states, scClassify2 achieves superior performance compared to other state-of-the-art methods. In addition to single-cell RNA-sequencing data, scClassify2 is generalizable to annotation from different platforms including subcellular spatial transcriptomics data. To facilitate ease of use, we provide a web server hosting over 30 human tissues.

bioinformatics↗

bioRxiv2024

Deciphering BRCAness Phenotype in Cancer: A Graph Convolutional Neural Network Approach with Layer-wise Relevance Propagation Analysis

BackgroundCancer variability among patients underscores the need for personalized therapy based on genomic understanding. BRCAness, characterized by vulnerabilities similar to BRCA mutations, particularly in homologous recombination repair, shows potential sensitivity to DNA-damaging agents like PARP inhibitors, highlighting its clinical significance. MethodsWe employed Graph Convolutional Neural Networks (GCNNs) with Layer-wise Relevance Propagation (LRP) to analyze gene expression data from the TCGA Pan-Cancer dataset. The study compared the efficacy of GCNNs against traditional machine learning models and differential gene expression analysis, focusing on their ability to elucidate complex genomic interactions defining BRCAness. ResultsDifferential Gene Expression (DGE) analysis proved limited in capturing the nuances of BRCAness. In contrast, GLRP significantly identified genes related to transcription regulation and cancer processes, emphasizing the phenotypes complexity. Gene Set Enrichment Analysis (GSEA) highlighted crucial pathways like Nuclear Receptors signaling, Cellular Senescence, and ESR-mediated signaling, underscoring their roles in BRCAness and therapeutic potential. ConclusionGLRP outperformed traditional approaches in analyzing BRCAness, providing deep insights into transcriptional and oncogenic processes critical to the BRCAness phenotype. Our findings suggest new directions for developing targeted and personalized cancer treatments, leveraging intricate molecular interactions associated with BRCAness.

bioinformatics↗

bioRxiv2024

The TissueTractor, a device for applying large strains to tissues and cells for simultaneous high-resolution live cell microscopy.

Mechanical strain substantially influences tissue shape and function in various contexts, from embryonic development to disease progression. Disruptions in these processes can result in congenital abnormalities and short-circuit mechanotransduction pathways. Manipulating strain in live tissues is crucial for understanding its impact on cellular and subcellular activities. Existing tools, such as optogenetic modulation of strain, are limited to small strain over limited distance and durations. Here, we introduce a high-strain stretcher system, the TissueTractor, designed for high-resolution spatiotemporal imaging of live tissues, enabling strain application varying from 0% to over 150%. This system is needed to unravel the intricate connections between mechanical forces and developmental processes. We demonstrated the stretcher with Xenopus laevis organotypic explants, human umbilical endothelial cells, and mouse neonatal cardiomyocytes to highlight the stretchers adaptability. These demonstrations underscore the potential of this stretcher to deepen our understanding of the mechanical cues governing tissue dynamics and morphogenesis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/600827v3_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@207163org.highwire.dtl.DTLVardef@1f424e7org.highwire.dtl.DTLVardef@1a2e9e1org.highwire.dtl.DTLVardef@a8d785_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Comprehensive mapping and modelling of the rice regulome landscape unveils the regulatory architecture underlying complex traits

Unraveling the regulatory mechanisms that govern complex traits is pivotal for advancing crop improvement. Here we present a comprehensive regulome atlas for rice (Oryza sativa), charting the chromatin accessibility across 23 distinct tissues from three representative varieties. Our study uncovers 117,176 unique open chromatin regions (OCRs), accounting for [~]15% of the rice genome, a notably higher proportion compared to previous reports in plants. Integrating RNA-seq data from matched tissues, we confidently predict 59,075 OCR-to-gene links, with enhancers constituting 69.54% of these associations, including many known enhancer-to-gene links. Leveraging this resource, we re-evaluate genome-wide association study results and discover a previously unknown function of OsbZIP06 in seed germination, which we subsequently confirm through experimental validation. We optimize deep learning models to decode regulatory grammar, achieving robust modeling of tissue-specific chromatin accessibility. This approach allows to predict cross-variety regulatory dynamics from genomic sequences, shedding light on the genetic underpinnings of cis-regulatory divergence and morphological disparities between varieties. Overall, our study establishes a foundational resource for rice functional genomics and precision molecular breeding, providing valuable insights into regulatory mechanisms governing complex traits.

genomics↗

bioRxiv2024

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis-- non-additive interactions between amino acid substitutions--and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable {beta}-subunit of tryptophan synthase (TrpB) in a non-native environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences--a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a new, large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling. Significance statementPredictive models for protein engineering seek to capture the relationship between protein sequence and function. While many methods and datasets exist for predicting the effects of single substitutions across a range of protein functions, fewer capture interactions among substitutions, which are much more difficult to predict. Even fewer do this comprehensively for a catalytic function. To provide a testbed for evaluating predictive models for enzyme engineering, we constructed and analyzed a 160,000-member enzyme sequence-fitness dataset at four interacting residues near the active site of tryptophan synthase, capturing significant non-additive effects of substitutions on catalytic function. It is necessary to predict and understand such interactions in order to efficiently traverse evolutionary landscapes and build machine learning models that accelerate protein engineering.

bioengineering↗

bioRxiv2024

Mature and migratory dendritic cells promote immune infiltration and response to anti-PD-1 checkpoint blockade in metastatic melanoma

Immune checkpoint inhibitors (ICIs) have heralded a remarkable shift in cancer care, significantly extending survival for advanced cancer patients. However, despite their remarkable clinical successes, a substantial majority of patients fail to achieve a lasting response to ICIs. To address this challenge and gain insights into the complex landscape of the tumor microenvironment (TME), we conducted an extensive analysis using single-cell RNA sequencing (scRNA; [~]216K cells across 39 samples) and single-nucleus transposase-accessible chromatin sequencing (snATAC; [~]43K cells from 15 samples) in a metastatic melanoma cohort. This systematic approach delineates 14 distinct cell types and 55 cell subtypes, including the identification of 15 transcriptional hallmarks of malignant cells. Through correlation analysis of cell subtype proportions, we unveiled six distinct clusters associated with varying tumor responses. Particularly intriguing was the identification of the mature DC enriched in immunoregulatory molecules (mregDC) subtype exhibiting correlations with naive T and B cells, forming an anti-tumor program that underscores the importance of multiple immune cell types in mediating anti-tumor immunity. Notably, we found that mregDC abundance represents a good prognostic predictor of progression-free survival (PFS) in the context of ICI treatment, and when combined with the TCF7+/- CD8 T cell ratio, it reliably predicts patient PFS across treatments beyond ICI. We validated our findings using an independent cohort of 274 ICI-treated melanoma samples analyzed using tissue-level expression. We next compared mregDCs and conventional dendritic cell types 1 and 2 (cDC1 and cDC2) using transcriptome signature, differentiation trajectory, interactome, cytokine milieu, and epigenome landscape analyses. This comparative analysis shed light on the unique attributes of mregDCs within the TME. Finally, we investigated cell type/subtype-specific genes, pathways, immune response enrichment, and ligand-receptor interactions closely associated with the proportions of mregDCs within the TME. These molecular and cellular insights, with their critical roles in enhancing the immune response against cancer, offer valuable prospects for predicting the efficacy of ICI regimens, and potentially guiding the selection of rational combinatorial therapies.

cancer biology↗

bioRxiv2024

Magnesium modulates phospholipid metabolism to promote bacterial phenotypic resistance to antibiotics

Non-inheritable antibiotic or phenotypic resistance ensures bacterial survival during antibiotic treatment. However, exogenous factors promoting phenotypic resistance are poorly defined. Here, we demonstrate that Vibrio alginolyticus are recalcitrant to killing by a broad spectrum of antibiotics under high magnesium. Functional metabolomics demonstrated that magnesium modulates fatty acid biosynthesis by increasing saturated fatty acid biosynthesis while decreasing unsaturated fatty acid production. Exogenous supplementation of unsaturated and saturated fatty acids increased and decreased bacterial susceptibility to antibiotics, respectively, confirming the role of fatty acids in antibiotic resistance. Functional lipidomics revealed that glycerophospholipid metabolism is the major metabolic pathway remodeled by magnesium, where phosphatidylethanolamine (PE) biosynthesis is reduced and phosphatidylglycerol (PG) production is increased. This process alters membrane composition, increasing membrane polarization, and decreasing permeability and fluidity, thereby reducing antibiotic uptake by V. alginolyticus. These findings suggest the presence of a previously unrecognized metabolic mechanism by which bacteria escape antibiotic killing through the use of an environmental factor.

microbiology↗

bioRxiv2024

A comparative study of the cryo-EM structures of S. cerevisiae and human anaphase-promoting complex/cyclosome (APC/C)

The anaphase-promoting complex/cyclosome (APC/C) is a large multi-subunit E3 ubiquitin ligase that controls progression through the cell cycle by orchestrating the timely proteolysis of mitotic cyclins and other cell cycle regulatory proteins. Although structures of multiple human APC/C complexes have been extensively studied over the past decade, the S. cerevisiae APC/C has been less extensively investigated. Here, we describe medium resolution structures of three S. cerevisiae APC/C complexes: unphosphorylated apo-APC/C and the ternary APC/CCDH1-substrate complex, and phosphorylated apo-APC/C. Whereas the overall architectures of human and S. cerevisiae APC/C are conserved, as well as the mechanism of CDH1 inhibition by CDK-phosphorylation, specific variations exist, including striking differences in the mechanism of coactivator-mediated stimulation of E2 binding, and the activation of APC/CCDC20 by phosphorylation. In contrast to human APC/C in which coactivator induces a conformational change of the catalytic module APC2:APC11 to allow E2 binding, in S. cerevisiae apo-APC/C the catalytic module is already positioned to bind E2. Furthermore, we find no evidence of a phospho-regulatable auto-inhibitory segment of APC1, that in the unphosphorylated human APC/C, sterically blocks the CDC20C-box binding site of APC8. Thus, although the functions of APC/C are conserved from S. cerevisiae to humans, molecular details relating to their regulatory mechanisms differ.

molecular biology↗

bioRxiv2024

The effects of 17α-estradiol treatment on endocrine system revealed by single-nucleus transcriptomic sequencing of hypothalamus

In this study, we investigated 17-estradiols role in lifespan extension from long-term administration. Pooled hypothalami from aged male Norway brown rats treated with 17-estradiol (O.T), aged male controls (O), and young male controls (Y) underwent single-nucleus transcriptomic sequencing (snRNA-seq). To evaluate the effects of 17-estradiol on aging neurons, supervised clustering of neurons based on neuropeptides and their receptors were used to evaluate the responses of each neuron subtype during aging and after 17-estradiol treatment. The elevated cellular metabolism, stress and decreased expression levels of pathways involved in synapse formation in neurons initiated by aging were significantly attenuated by 17-estradiol. Assessment of changes in neuron populations showed that neurons related to food intake, reproduction, blood pressure, stress response, and electrolyte balance were sensitive to 17-estradiol treatment. 17-estradiol treatment not only increased serum Oxytocin (Oxt), but also heightened the activity of hypothalamic-pituitary-gonadal (HPG) axis, as evidenced by significantly elevated levels of plasma Gnrh, total testosterone, and decreased estradiol. Elevated Gnrh1 was confirmed to be one of the causal effects mediating the role of 17-estradiol in energy homeostasis, neural synapse, and stress response. Notably, Crh neurons exhibited prominent stressed phenotype in O.T, distinct to appetite-stimulating neurons Agrp and Ghrl. Therefore, the HPG axis and energy metabolism may be key targets of 17-estradiol in male hypothalamus. Additionally, supervised clustering of neurons was shown to be a useful method for assessing treatment responses and cellular perturbation among different neuron subtypes in the hypothalamus.

neuroscience↗

bioRxiv2024

PTBP1 mediates Sertoli cell actin cytoskeleton organization by regulating alternative splicing of actin regulators

Spermatogenesis is a biological process within the testis that produces haploid spermatozoa for the continuity of species. Sertoli cells are somatic cells in the seminiferous epithelium that orchestrate spermatogenesis. Cyclic reorganization of Sertoli cell actin cytoskeleton is vital for spermatogenesis, but the underlying mechanism remains largely unclear. Here, we report that RNA-binding protein PTBP1 controls Sertoli cell actin cytoskeleton reorganization by programming alternative splicing of actin cytoskeleton regulators. This splicing control enables ectoplasmic specializations, the actin-based adhesion junctions, to maintain the blood-testis barrier and support spermatid transport and transformation. Particularly, we show that PTBP1 promotes actin bundle formation by repressing the inclusion of exon 14 of Tnik, a kinase present at the ectoplasmic specialization. Our results thus reveal a novel mechanism wherein Sertoli cell actin cytoskeleton dynamics is controlled post-transcriptionally by utilizing functionally distinct isoforms of actin regulatory proteins, and PTBP1 is a critical regulatory factor in generating such isoforms.

molecular biology↗

bioRxiv2024

A spontaneous mutation in ADIPOR1 causes retinal degeneration in mice

Adiponectin receptor 1 (ADIPOR1) is a transmembrane protein necessary for normal anatomy and physiology in the retina. In a recent study of complement factor H knockout mice (Cfh-/-), our lab discovered a flecked retina phenotype and retinal thinning by fundus imaging and optical coherence tomography (OCT), respectively. The phenotype was observed in a subset (50%) of Cfh-/- mice. The thinning observed in vivo is due to an early degeneration of rod photoreceptors. This phenotype has not been reported in published studies of Cfh-/- mice. AdipoR1 knockout mice (AdipoR1-/-) and mice deficient in Membrane Frizzled Related Protein (MFRP) exhibit this phenotype, suggesting an involvement in the emergence of the retinal degeneration observed in a subset of Cfh-/- mice. Cfh and AdipoR1 are located in close proximity on mouse Chromosome 1 (Chr1) and a complementation cross between Cfh and AdipoR1 mice with retinal degeneration produced 100% progeny with retinal degeneration. Sequencing of the Cfh-/- mice revealed a c.841 C > T mutation in AdipoR1. Furthermore, one Cfh wildtype (of Cfh+/+) and 2 heterozygous (of Cfh+/-) mice exhibited retinal degeneration and were homozygous for the point mutation. The c.841 C > T mutation results in a proline to serine conversion at position 281 (P281S) in ADIPOR1. This residue is critical for ADIPOR1 open and closed conformations in the membrane. In silico modeling of candidate ADIPOR1 ligands, 11-cis-retinaldehyde and docosahexaenoic acid (DHA), that are deficient in AdipoR1-/-, suggests that ADIPOR1 is involved in trafficking retinoids and fatty acids and their combined deficiency in the ADIPOR1 mutant retinas might explain the retinal degeneration phenotype.

neuroscience↗