Biology subjects

Pu, M.

Publications and source records attributed to Pu, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Slow breathing impacts inter-organ dynamics modulating brain function and risk behavior

Successful decision-making requires that external information be interpreted in the context of the bodys state. Within the framework of body-brain interaction, deliberately modifying ones autonomic state can shape how we evaluate the world, ultimately influencing choices. Yet, it remains unclear whether and how intentional autonomic regulation affects human decision-making. In this study, we tested instructed prolonged exhalation, a slow-breathing technique designed to boost parasympathetic activity during risky decision-making. Participants followed distinct breathing protocols while making risky choices, with neural and physiological activity measured using fMRI and multi-channel monitoring. Prolonged exhalation increased risky choices by enhancing reward sensitivity and elevating cardiac parasympathetic activity. Importantly, individuals with greater parasympathetic upregulation also showed stronger reward-related responses in the ventromedial prefrontal cortex and precuneus. Our work reveals a transformative role for breathing-based interventions, demonstrating that breathing-based autonomic regulation can shape value-based decision-making through neuro-cardiac pathways. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/698695v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@190293corg.highwire.dtl.DTLVardef@1835c63org.highwire.dtl.DTLVardef@1267ff3org.highwire.dtl.DTLVardef@9a583e_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIProlonged exhalation increases risky decisions by increasing the reward sensitivity C_LIO_LIProlonged exhalation enhances cardiac parasympathetic activity without dampening sympathetic activities C_LIO_LIGreater cardiac parasympathetic activity under prolonged exhalation amplifies neural reward sensitivity in the ventromedial prefrontal cortex and precuneus C_LI

neuroscience↗

bioRxiv2026

Neuro-metabolic pathways of high-protein meal reducing food craving

Across species, high-protein foods have been shown to reduce appetite throughout the day. Although higher protein intake alters multiple metabolic responses, the exact neuro-metabolic mechanisms underlying food craving remain unclear. Here, we investigated whether a protein-rich diet modulates plasma tyrosine dynamics, the precursor of dopamine, thereby altering dopaminergic brain activity and reducing food craving in humans. In this within-subject, cross-over study, 30 healthy participants (age, Mean=23.63, SD=3.23 years) were provided with either a high- or low-protein/carbohydrate breakfast. Three and a half hours after breakfast, participants viewed high-or low caloric food images while undergoing magnetic resonance imaging (MRI), and their subjective food craving was assessed using the validated Food Craving Questionnaire- State version. Through the experimental procedure, plasma tyrosine levels were continuously monitored. Our results show that the high-protein/carbohydrate breakfast significantly enhanced plasma tyrosine levels, which were negatively associated with subjective food craving several hours after meal intake. Importantly, we observed significantly stronger midbrain activity following the high-protein/carbohydrate breakfast, which was associated with greater reduction in subjective food craving. Furthermore, we analyzed brain gradients that characterize spatial patterns of large-scale neural activity, allowing us to examine the entire process underlying dietary choices at the whole-brain level. Compared with the low-protein/carbohydrate breakfast, the high-protein/carbohydrate breakfast reduced whole-brain functional reorganization, indicating lower neural sensitivity to high- versus low-caloric food stimuli. Notably, the degree of this high-protein/carbohydrate induced brain-state shift was related to the reduction in food craving. Together, these results provide strong evidence that high-protein/carbohydrate meals modulate dopaminergic mechanisms and large-scale whole-brain neural reorganization, contributing to reduced food craving throughout the day in humans.

neuroscience↗

bioRxiv2025

Homodimerized Arpins: Binding to Arp2/3 Complexes with Positive Synergy to Inhibit Lamellipodia-Dependent Tumor Metastasis

The Arp2/3 complex is a central regulator of actin polymerization dynamics and cancer cell motility, with its dysregulation implicated in metastasis and therapeutic resistance. Despite its therapeutic potential, targeting Arp2/3 remains challenging due to the lack of precise molecular insights into endogenous inhibitors. Arpin, a lamellipodia-localized Arp2/3 inhibitor, has emerged as a critical modulator of cancer migration; however, the structural and mechanistic basis of its inhibitory function remains unresolved. Here, we report the 1.65-[A] crystal structure of Arpins N-terminal globular domain, revealing a unique structural fold distinct from all known Arp2/3-binding factors. Structural and biophysical analyses demonstrate that Arpin forms homodimers via a conserved interface, which is essential for cooperative inhibition of Arp2/3-dependent actin polymerization. Functional studies in cancer models reveal that Arpin homodimerization potently suppresses lamellipodia-driven migration and invasion, effects further enhanced by engineered dimeric constructs or artificially designed dual-tailed peptides. These findings elucidate a structural basis for Arpin-mediated suppression of cancer cell motility and identify homodimeric cooperativity as a druggable mechanism for targeting metastatic progression. Our work provides a molecular framework for designing Arpin-inspired inhibitors to counteract therapeutic resistance and metastasis in cancers reliant on Arp2/3-driven actin dynamics.

cancer biology↗

bioRxiv2025

Robust and Reliable de novo Protein Design: A Flow-Matching-Based Protein Generative Model Achieves Remarkably High Success Rates

Generative models have achieved significant progress in the field of protein design, particularly in the generation of tertiary structures. However, they still face several challenges, such as balancing the designability and diversity of the generated structures, generating specified structures under highly constrained conditions, and the most challenging aspect, direct functional design such as motifs and binders. We present OriginFlow, an efficient protein generative model that combines Stochastic Differential Equation (SDE) models and flow models based on flow matching. The generated structures exhibit state-of-the-art (SOTA) levels of designability, diversity, and novelty. Moreover, this model demonstrates outstanding performance in functional design aspects such as motifs, binders, and symmetric motif scaffolding. We performed binder design for multiple targets, and all results showed excellent affinity performance in AF3 complex predictions and MD experiments. Wet-lab validation was conducted on PD-L1, RBD, and VEGF targets, achieving 90% expression, solubility, and affinity. These results are significantly superior to all current AI binder design algorithms.

bioengineering↗

bioRxiv2024

ELO-6 expression predicts longevity in isogenic populations of Caenorhabditis elegans

Variations of individual lifespans within genetically identical populations in homogenous environments are remarkable, with the cause largely unknown. Gene expression changes with age, and the transcriptome changes correlate with chronological aging. Here, we show that in Caenorhabditis elegans, the expression dynamic of the fatty acid elongase ELO-6 during aging predicts individual longevity in isogenic populations. The expression of elo-6 is reduced with age. From adult day 5, ELO-6 expression level exhibits variation between individuals, and the expression level is positively correlated with adult lifespan and health span. Interventions that prolong longevity enhance the expression stability of ELO-6 during aging from adult day 4 to adult day 8, indicating ELO-6 is also a populational lifespan predictor. We performed transcriptome analysis in short-lived and long-lived isogenic worms and identified differentially expressed genes, which are enriched for PQM-1 binding sites. Decreasing pqm-1 expression in young adults improved the homogeneity of ELO-6 levels between individuals and enhanced health span. Furthermore, we found reducing the expression of genes that are highly expressed in short-lived individuals, including PQM-1 target genes, enhanced ELO-6 expression stability with age and extended lifespan. Thus, our study identified ELO-6 as a predictor of individual and populational lifespan and revealed the role of pqm-1 in restricting health span and possibly causing individual lifespan variation.

physiology↗

bioRxiv2023

Cell context-specific Synthetic lethality Prediction and Mechanism Analysis

Synthetic lethality (SL) holds significant promise as a targeted cancer therapy by selectively eliminating tumor cells while sparing normal cells. However, the discovery of SL gene pairs has encountered tremendous challenges, including high costs and low efficiency of experimental methods. Current computational approaches only provide limited insights because of overlooking the crucial aspects of cellular context dependency and mechanistic understanding of SL pairs. To overcome these challenges, we have developed SLWise, a deep-learning model capable of predicting SL interactions in diverse cellular backgrounds. We evaluated SLWise using a real world ground truth standard. The evaluation demonstrated that SLWise outperformed benchmark models in SL prediction. Additionally, we proposed a novel analysis scheme called SLAD-CE (Synthetic Lethal Associated Gene Detection and Cell Damage Evaluation) for the identification of abnormal essential genes induced by SL gene pairs and tracking the extent of cell damage. Leveraging the cell-line-specific input feature L1000 and employing Gene Set Enrichment Analysis (GSEA), SLAD-CE provides valuable insights into the underlying mechanisms of SLWise-predicted gene pairs. The combined utilization of SLWise and SLAD-CE offers an approach for predicting and analyzing SL interactions in specific cellular contexts. Our findings highlight the potential of SLWise and SLAD-CE in advancing SL-based therapies by improving prediction accuracy and enhancing mechanistic understanding, ultimately contributing to the development of effective precision treatments for cancer.

cancer biology↗

bioRxiv2023

Sparse Modeling of Genomic Landscape Identifies Pathogenic Processes and Therapeutic Targets in Metastatic Breast Cancer

Breast cancer is a heterogeneous disease and ranks as one of the most lethal and frequently detected disease in the world. It poses significant challenges for precision therapy. To better decipher the patterns of heterogeneous nature in human genome and converge them into common functionals, mutational signatures are introduced to define the types of DNA damage, repair and replicative mechanisms that shape the genomic landscape of each cancer patient. In this study, we developed a deep learning (DL) model, MetaWise 2.0, based on pruning technology that improved model generalization with deep sparsity. We applied it to patient samples from multiple sequencing studies, and identified statistically significant mutational signatures associated with metastatic progression using Shapley additive explanations (SHAP). We also employed gene cumulative contribution abundance analysis to link the mutational signatures with relevant genes, which could unearth the shared molecular mechanisms behind tumorigenesis and metastasis of each patient and lead to novel therapeutic target identification. Our study illustrates that MetaWise 2.0 is an effective DL tool for discovering clinically meaningful mutational signatures in metastatic breast cancer (MBC) and relating them directly to relevant biological functions and gene targets. These findings could facilitate the development of novel therapeutic strategies and improve the clinical outcomes for individual patients.

bioinformatics↗

bioRxiv2023

Using graph-based model to identify cell specific synthetic lethal effects

Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cells survival. This makes SL pairs attractive targets for precision cancer therapies, as targeting the unimpaired gene of the SL pair can selectively kill cancer cells that already harbor the impaired gene. Limited by the difficulty of finding true SL pairs, especially on specific cell types, the identification of SL targets still relies on expensive, time-consuming experimental approaches. In this work, we utilized various cell-line specific omics data to design a deep learning model for predicting SL pairs on particular cell-lines. By incorporating multiple types of cell-specific omics data with a self-attention module, we represent gene relationships as graphs. Our approach demonstrates the potential to facilitate the discovery of cell-specific SL targets for cancer therapeutics, providing a tool to unearth mechanisms underlying the origin of SL in cancer biology. Our approach allows for prediction of SL pairs in a cell-specific manner and enhances cancer precision medicine. The code and data of our approach can be found at https://github.com/promethiume/SLwise HighlightsO_LIFew computational methods can systematically predict SL pairs at a cell-specific level, and their performance may not generalize well to clinical scenarios due to the heterogeneity of cancer types. C_LIO_LIThe SLWise utilizes various cell-line specific omics data to design a deep learning model with a graph-based representation and self-attention mechanism. C_LIO_LIThis approach allows for the prediction of SL pairs in a cell-specific manner, providing valuable insights on effectively identifying the cell-type specific SL targets for personalized treatment strategies. C_LI

bioinformatics↗

bioRxiv2022

Treatment of pancreatic cancer with irreversible electroporation and intratumoral CD40 antibody stimulates systemic immune responses that inhibit liver metastasis in an orthotopic model.

BackgroundPancreatic cancer (PC) has a poor prognosis, and most patients present with either locally advanced or distant metastatic disease. Irreversible Electroporation (IRE) is a non-thermal method of ablation used clinically in locally advanced PC, but most patients eventually develop distant recurrence. We have previously shown that IRE alone is capable of generating protective, neoantigen-specific immunity. Here we aim to generate meaningful therapeutic immune effects by combining IRE with local (intratumoral) delivery of a CD40 agonistic antibody (CD40Ab). MethodsKPC46 organoids were generated from a tumor-bearing male KrasLSL-G12D-p53LSL-R172H-Pdx-1-Cre (KPC) mouse. Orthotopic tumors were established in the pancreatic tail of B6/129 F1J mice via laparotomy. Mice were randomized to treatment with either sham laparotomy, IRE alone, CD40Ab alone, or IRE followed immediately by CD40Ab injection. Metastatic disease and immune infiltration in the liver were analyzed 14 days post-procedure using flow cytometry and multiplex immunofluorescence imaging with spatial analysis. Candidate neoantigens were identified by mutanome profiling of tumor tissue for ex vivo functional analyses. ResultsThe combination of IRE+CD40Ab improved median survival to greater than 35 days, significantly longer than IRE (21 days) or CD40Ab (24 days) alone (p<0.01). CD40Ab decreased metastatic disease burden, with less disease in the combination group than in the sham group or IRE alone. Immunohistochemistry of liver metastases revealed a more than two-fold higher infiltration of CD8+ T-cells in the IRE+CD40Ab group than in any other group (p<0.01). Multiplex immunofluorescence imaging revealed a 4-6-fold increase in the density of CD80+CD11c+ activated dendritic cells (p<0.05), which were spatially distributed throughout the tumor unlike the sham group, where they were restricted to the periphery. In contrast, CD4+FoxP3+ T-regulatory cells (p<0.05) and Ly6G+ MDSCs (P<0.01) were reduced and restricted to the tumor periphery in the IRE+CD40Ab group. T-cells from the IRE+CD40Ab group recognized significantly more peptides representing candidate neoantigens than did T-cells from the IRE or untreated control groups. ConclusionsIRE can induce local tumor regression and neoantigen-specific immune responses. Addition of CD40Ab to IRE improved dendritic cell activation and neoantigen recognition, while generating a strong systemic anti-tumor T-cell response that inhibited metastatic disease progression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/510847v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1a42713org.highwire.dtl.DTLVardef@16be8org.highwire.dtl.DTLVardef@15362eaorg.highwire.dtl.DTLVardef@182f988_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Deep Learning model accurately classifies metastatic tumors from primary tumors based on mutational signatures

Metastatic propagation is the leading cause of death for most cancers. Prediction and elucidation of metastatic process is crucial for the therapeutic treatment of cancers. Even though somatic mutations have been directly linked to tumorigenesis and metastasis, it is less explored whether the metastatic events can be identified through genomic mutation signatures, a concise representation of the mutational processes. Here, applying mutation signatures as input features calculated from Whole-Exome Sequencing (WES) data of TCGA and other metastatic cohorts, we developed MetaWise, a Deep Neural Network (DNN) model. This model accurately classified metastatic tumors from primary tumors. Signatures of non-coding mutations also have a major impact on the model performance. SHapley Additive exPlanations (SHAP) and Local Surrogate (LIME) analysis into the MetaWise model identified several mutational signatures directly correlated to metastatic spread in cancers, including APOBEC-mutagenesis, UV-induced signatures and DNA damage response deficiency signatures.

cancer biology↗

bioRxiv2022

Pathogen effector-associated nuclear-localization of RPW8.2 amplifies its expression to boost immunity in Arabidopsis

RESISTANCE TO POWDERY MILDEW 8 (RPW8) defines a unique N-terminal coiled-coil domain of nucleotide-binding and leucine-rich repeat immune receptors required for immune signaling in plants. Arabidopsis RPW8.2 is specifically induced by the powdery mildew (PM) fungus (Golovinomyces cichoracearum) in the infected epidermal cells to activate immunity. The mechanism of RPW8.2-induction is not well understood. Here, we identify a G. cichoracearum factor delivered to the nucleus of the host cell, named Gc-RPW8.2 interacting protein 1 (GcR8IP1). Ectopic expression of GcR8IP1 in Arabidopsis or Nicotiana benthamiana suppressed host immune responses and enhanced susceptibility to PM. Host-induced gene silencing of GcR8IP1 compromised PM infectivity in susceptible Arabidopsis plants. Co-expression of GcR8IP1 with RPW8.2 increased nuclear localization of RPW8.2, which in turn, promoted transcriptional amplification of RPW8.2. Thus, RPW8.2-dependent defense strengthening is due to altered partitioning of RPW8.2 by an effector of a PM fungus, which exemplifies an atypical form of effector-triggered immunity.

plant biology↗

bioRxiv2022

LLPSWise - fast and accurate prediction of LLPS constituents

The recent discovery of different types of biological liquid-liquid phase separation (LLPS) systems presents enormous opportunities to uncover underlying biological mechanisms from a single-molecule level to mesoscopic scales and beyond. While progress has been made on the front of computational prediction of LLPS propensity of proteins, the constituent identification of LLPS systems continues to be a pertinent issue that has yet to be addressed. Compiled evidence indicates that the biological mechanism of LLPS involves the employment of different biomolecules into their liquid-liquid separation phase. Since constituent identification relies on experimental approaches, the process is arduous and inefficient. Here, we propose a sequence based LLPS propensity prediction method and scan the human proteome and biochemical pathways to establish a systematic biological view of LLPS. Additionally, we present a fast, accurate method for identifying the constituents of LLPS systems. The source code for our method is available via https://github.com/promethiume/LLPSWise

bioinformatics↗

bioRxiv2021

Molecular mechanisms governing circulating immune cell heterogeneity across different species revealed by single cell sequencing

BackgroundImmune cells play important roles in mediating immune response and host defense against invading pathogens. However, insights into the molecular mechanisms governing circulating immune cell diversity among multiple species are limited. MethodsIn this study, we compared the single-cell transcriptomes of 77{square}957 immune cells from 12 species using single-cell RNA-sequencing (scRNA-seq). Distinct molecular profiles were characterized for different immune cell types, including T cells, B cells, natural killer cells, monocytes, and dendritic cells. ResultsResults revealed the heterogeneity and compositions of circulating immune cells among 12 different species. Additionally, we explored the conserved and divergent cellular crosstalk and genetic regulatory networks among vertebrate immune cells. Notably, the ligand and receptor pair VIM-CD44 was highly conserved among the immune cells. ConclusionsThis study is the first to provide a comprehensive analysis of the cross-species single-cell atlas for peripheral blood mononuclear cells (PBMCs). This research should advance our understanding of the cellular taxonomy and fundamental functions of PBMCs, with important implications in evolutionary biology, developmental biology, and immune system disorders.

cell biology↗

bioRxiv2021

Screening of cell-virus, cell-cell, gene-gene interactions among kingdoms of life at single cell resolution

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) issued a significant and urgent threat to global health. The exact animal origin of SARS-CoV-2 remains obscure and understanding its host range is vital for preventing interspecies transmission. Previously, we have assessed the target cell profiles of SARS-CoV-2 in pets, livestock, poultry and wild animals. Herein, we expand this investigation to a wider range of animal species and viruses to provide a comprehensive source for large-scale screening of potential virus hosts. Single cell atlas for several mammalian species (alpaca, hamster, hedgehog, chinchilla etc.), as well as comparative atlas for lung, brain and peripheral blood mononuclear cells (PBMC) for various lineages of animals were constructed, from which we systemically analyzed the virus entry factors for 113 viruses over 20 species from mammalians, birds, reptiles, amphibians and invertebrates. Conserved cellular connectomes and regulomes were also identified, revealing the fundamental cell-cell and gene-gene cross-talks between these species. Overall, our study could help identify the potential host range and tissue tropism of SARS-CoV-2 and a diverse set of viruses and reveal the host-virus co-evolution footprints.

cell biology↗

bioRxiv2021

Insights into the susceptibility of rice to a floral disease

Crop floral diseases are economically important as they reduce grain yield and quality and even introduce food toxins. Rice false smut has emerged as a serious floral disease producing mycotoxins. However, very little is known on the interaction mechanisms between rice flower and the causal fungus Ustilaginoidea virens. Here we show that a conserved anti-fungal immunity in rice flower is disarmed by U. virens via a secreted protein UvChi1. UvChi1 functioned as an essential virulence factor and directly interacted with the chitin receptor CEBiP and co-receptor CERK1 in rice to disrupt their oligomerizations and subsequent immune responses. Moreover, intraspecific-conserved UvChi1 could target OsCEBiP/OsCERK1 receptor complex in at least 98.5% of 5232 surveyed rice accessions. These results demonstrate that U. virens utilizes a crucial virulence factor to subvert chitin-triggered flower immunity in most rice varieties, providing new insights into the susceptibility of rice to false smut disease. One Sentence SummaryThe fungal pathogen Ustilaginoidea virens disarms chitin-triggered immunity in rice flower via a secreted chitinase.

plant biology↗

bioRxiv2021

Proteasome maturation factor UMP1 confers broad-spectrum disease resistance by modulating H2O2 accumulation in rice

Crops with broad-spectrum resistance (BSR) to diseases are highly desirable in agricultural production. Identification of BSR loci and dissection of the underlying mechanisms are fundamental for crop resistance breeding. Here, we describe the identification and characterization of a rice UMP1 allele, which confers race-nonspecific BSR against blast pathogen Magnaporthe oryzae. OsUMP1 encodes a proteasome maturation factor that contributes to 26S proteasome abundance and activity in rice. Modulation of OsUMP1 expression leads to proteome changes, particularly affects the amounts and activities of H2O2-degrading enzymes. Consequently, H2O2 accumulation and disease resistance are enhanced in OsUMP1-overexpressing rice but reduced in loss-of-function mutants. Elevation of OsUMP1 expression also promotes rice resistance to foliar pathogens Rhizoctonia solani and Xanthomonas oryzae pv. oryzae and a floral pathogen Ustilaginoidea virens without observable yield penalty. These results indicate a BSR pathway linking the proteasome machinery and H2O2 homeostasis, and provide a candidate gene for balancing BSR and yield traits in rice breeding. One Sentence SummaryA natural allele of rice UMP1 promotes resistance to multiple pathogens by boosting H2O2 accumulation.

plant biology↗

bioRxiv2021

Locus-specific H3K9me3 gain in aged somatic tissues in Caenorhabditis elegans

Epigenetic alterations occur as organisms age, and lead to chromatin deterioration, loss of transcriptional silencing and genomic instability. Dysregulated epigenome has been linked to increased susceptibility to age-related disorders. We aim to characterize the age-dependent changes of the epigenome and, in turn, to understand epigenetic processes that drive aging phenotypes. In this study, we focused on the aging-associated changes in the repressive histone marks H3K9me3 and H3K27me3 in C. elegans. We observed redistribution of of both histone marks, but the changes are more significant for H3K9me3. We further found alteration of heterochromatic boundaries in aged somatic tissues. Interestingly, we discovered that the most significant changes reflected H3K9me3-marked regions that are formed during aging, and are absent in developing worms, which we termed "aging-associated repressive domains" (AARDs). These AARDs preferentially occur in genic regions that are marked by high levels of H3K9me2 and H3K36me2 in larval stages. Interestingly, maintenance of high H3K9me2 levels in these regions have been shown to correlate with longer lifespan. Next, we examined whether the changes in repressive histone marks lead to de-silencing of repetitive DNA elements, as reported for several other organisms. We observed increased expression of active repetitive DNA elements but not global re-activation of silent repeats in old worms, likely due to the distributed nature of repetitive elements in the C. elegans genome. Intriguingly, CELE45, a putative short interspersed nuclear elements (SINE), was greatly overexpressed at old age and upon heat stress. SINEs have been suggested to regulate transcription in response to various cellular stresses in mammals, it is likely that CELE45 RNAs also play roles in stress response and aging in C. elegans. Taken together, our study revealed significant and specific age-dependent changes in repressive histone modifications and repetitive elements, providing important insights into aging biology. Author summaryHeterochromatin refers to the portion of the genome that is tightly packed where genes stay silent. Heterochromatin is typically decorated by particular chemical groups called histone modifications, such as trimethylation of lysine 9 or lysine 27 on histone 3 (H3K9me3 or H3K27me3). To understand how the heterochromatin landscape may change from a "youthful" to an "aged" state, we monitored the genome-wide patterns of H3K9me3 and H3K27me3 during aging using the genetic model soil worm C. elegans. We found that while H3K27me3 remained relatively stable with age, H3K9me3 showed profound genome-wide redistribution in aged worms. We observed that new H3K9me3-marked heterochromatin preferentially formed in specific gene-rich regions in aged worms. Interestingly, these particular regions were marked by high levels of three other histone modifications when worms were young. This result suggested that H3K9me3 gain during aging is influenced by the gene-specific landscape of histone modifications established at young age rather than occurs in a stochastic manner. In summary, our study discovered reproducible and gene-specific changes in histone modifications that likely contribute to the aging phenotypes.

genomics↗

bioRxiv2020

bHLH11 negatively regulates Fe homeostasis by its EAR motifs recruiting corepressors in Arabidopsis

Iron (Fe) homeostasis is essential for plant growth and development. Many transcription factors play pivotal roles in the maintenance of Fe homeostasis. bHLH11 was identified as a negative transcription factor regulating Fe homeostasis, however, the underlying molecular mechanism remains elusive. We generated two loss-of-function bhlh11 mutants which display the enhanced sensitivity to Fe excess, the increased Fe accumulation and the elevated expression of Fe deficiency responsive genes. bHLH11 protein, localized in both the cytoplasm and nucleus, decreases in response to Fe deficiency. Coexpression assays indicate that bHLH IVc transcription factors (TFs) (bHLH34, bHLH104, bHLH105, and bHLH115) facilitate the nuclear accumulation of bHLH11 protein. Further analysis indicates that bHLH11 represses the transactivity of bHLH IVc TFs towards bHLH Ib genes (bHLH38, bHLH39, bHLH100, and bHLH101). bHLH11 contains two EAR motifs which are responsible for the repression function by recruiting the TOPLESS/TOPLESS-RELATED (TPL/TPRs) corepressors. Correspondingly, the expression of Fe uptake genes increases in the tpr1 tpr4 tpl mutant. Moreover, genetic analysis reveals that bHLH11 has functions independent of FIT. This study provides insights into the complicate Fe homeostasis signaling network. One-sentence summarybHLH IVc proteins promote the bHLH11 protein accumulation in the nucleus where bHLH11 inhibits the transcriptional activation ability of bHLH IVc via its EAR motifs recruiting the TOPLESS/TOPLESS-RELATED corepressors.

plant biology↗