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Zhao, Y.

Publications and source records attributed to Zhao, Y..

At least 523 records · Page 29Linked to original sources
bioRxiv2024

Endothelial PHD2 deficiency induces apoptosis resistance and inflammation via AKT activation and AIP1 loss independent of HIF2α

BACKGROUNDIn hypoxic and pseudohypoxic rodent models of pulmonary arterial hypertension (PAH), hypoxia-inducible factor (HIF) inhibition reduces disease severity. However, HIF activation alone, due to genetic alterations or use of inhibitors of prolyl hydroxylase domain (PHD) enzymes, has not been definitively shown to cause PAH in humans, indicating the involvement of other mechanisms. METHODSPseudohypoxia was investigated in primary human lung endothelial cells by silencing PHD2, and in Tie2-Cre/Phd2 knockout mice, a rodent model of PAH. Lung vascular endothelial cells from PAH patients, and lung tissue from both SU5416/hypoxia PAH rats and PAH patients, were examined for validation. RESULTSPHD2 silencing or inhibition, while activating HIF2, induces apoptosis-resistance, hypo-proliferation, and IFN/STAT activation in endothelial cells, independent of HIF signaling. Mechanistically, PHD2 deficiency activates AKT and ERK, inhibits JNK, and reduces AIP1 (ASK1-interacting protein 1), all independent of HIF2. Like PHD2, AIP1 silencing affects these same kinase pathways and produces a similar dysfunctional endothelial cell phenotype, which can be partially reversed by AKT inhibition. These findings are corroborated in lung tissues of rodent PAH models and pulmonary vascular endothelial cells and tissues from PAH patients. CONCLUSIONSPHD2 deficiency in lung vascular endothelial cells induces an apoptosis-resistant, inflammatory, and hypo-proliferative phenotype. AKT activation and AIP1 loss, but not HIF signaling, drive these aberrant phenotypic changes. Our study suggests that HIF blockade alone may not suffice for PAH therapy; targeting PHD2, AKT, and AIP1 has the potential for developing more effective treatment. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/578286v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1fd0a0borg.highwire.dtl.DTLVardef@19e6ba9org.highwire.dtl.DTLVardef@1ae2827org.highwire.dtl.DTLVardef@ce31ec_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIPHD2 silencing in human lung vascular endothelial cells suppresses apoptosis, inhibits proliferation, and activates STAT signaling, effects that persist despite HIF2 inhibition or knockdown. C_LIO_LIPHD2 silencing activates AKT and ERK, inhibits JNK, and decreases AIP1, all independently of HIF2 C_LIO_LILike PHD2, AIP1 silencing led to similar alterations in kinase signaling and endothelial cell phenotypes, which are partially reversed by ATK inhibition. C_LIO_LIThese in vitro findings align with observations in lung vascular endothelial cells and tissues from rodent models of PAH as well as PAH patients. C_LI

cell biology↗
bioRxiv2024

A neutral process of genome reduction in marine bacterioplankton

Marine bacterioplankton communities are dominated by cells equipped with small genomes. Streamlining selection has been accepted as the main force driving their genome reduction. Here, we report that a neutral evolutionary mechanism governs genome reduction in the Roseobacter group that represents 5-20% of the bacterioplankton cells in coastal waters. Using representative strains that fall into three genome size groups (2-3, 3-4, and 4-5 Mbp), we measured their genomic mutation rates () through long-term mutation accumulation experiments followed by genome sequencing the resulting 437 mutant lines. We further calculated their effective population sizes (Ne) based on and the neutral genetic diversity of the studied species, the latter estimated based on multiple genome sequences of natural isolates collected from global oceans with their population structure considered. A surprising finding is that Ne scales positively with genome size, which is the opposite of the expectation from the streamlining selection theory. As the strength of random genetic drift is the inverse of Ne, this result instead suggests drift as the primary driver of genome reduction. Additionally, we report a negative scaling between and genome size, which is the first experimental evidence for the long-lasting hypothesis that mutation rate increases play a part in marine bacterial genome reduction. As scales inversely with Ne, genetic drift appears to be the ultimate cause of genome reduction in these Roseobacters. Our finding discounts, but is insufficient to reject, the streamlining theory because streamlining process is expected to be more effective in oligotrophic open ocean waters.

microbiology↗
bioRxiv2024

Cost-benefit analysis of cryogenic electron tomography subtomogram averaging of chaperonin MmCpn at near atomic resolution.

Cryogenic electron microscopy single particle reconstruction (cryoEM-SPR) has evolved into a routine approach for determining macromolecule structures to near-atomic resolution. Cryogenic electron tomography subtomogram averaging (cryoET-STA) towards similar resolution, in contrast, is still under active development. CryoET can capture the 3D snapshot of individual macromolecules by stage tilting, offering multiple angular views per particle than the single particle reconstruction approach. Here we use the archaea chaperonin MmCpn as a model macromolecule to investigate the resolution limiting factors of cryoET-STA in terms of cumulative electron dose, ice thickness, subtomogram numbers and tilt angle ranges. By quantitative analysis of these factors against the STA reconstruction resolution, we delineate the feasibility of attaining high resolution structure determination with cryoET-STA. This study provides biophysical guidance for the application of cryoET-STA towards high resolution and the cost against benefit of using cryoET-STA to achieve an efficient outcome at the desired resolution.

biophysics↗
bioRxiv2024

Activated fibroblasts drive cellular interactions in end-stage pediatric hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a relatively rare but debilitating diagnosis in the pediatric population and patients with end-stage HCM require heart transplantation. In this study, we performed single-nucleus RNA sequencing on pediatric HCM and control myocardium. We identified distinct underling cellular processes in pediatric, end-stage HCM in cardiomyocytes, fibroblasts, endothelial cells, and myeloid cells, compared to controls. Pediatric HCM was enriched in cardiomyocytes exhibiting "stressed" myocardium gene signatures and underlying pathways associated with cardiac hypertrophy. Cardiac fibroblasts exhibited clear activation signatures and heightened downstream processes associated with fibrosis, more so than adult counterparts. There was notable depletion of tissue-resident macrophages, and increased vascular remodeling in endothelial cells. Our analysis provides the first single nuclei analysis focused on end-stage pediatric HCM.

genomics↗
bioRxiv2024

The integrated stress response/eIF2α pathway controls cytokine production in tissue-resident memory CD4+ T cells

Tissue-resident memory T (Trm) cells are a specialized T cell population that resides in tissues and can play both a protective and pathogenic role. The mechanism that enables Trm cells to provide a rapid protective response while restricting their function in homeostasis remains unclear. Here, we show that human and mouse CD4+ Trm cells exist in a poised state, characterized by storage of proinflammatory type-1 and type-3 cytokine mRNAs without protein production. In steady-state conditions, cytokine mRNA translation in Trm cells is suppressed by the integrated stress response (ISR)/eIF2 pathway, whereas Trm-cell activation under inflammatory conditions results in eIF2 dephosphorylation, leading to derepression and rapid translation of the cytokine mRNAs stored in stress granules. Pharmacological inhibition of eIF2 dephosphorylation resulted in reduced cytokine production from Trm cells, and ameliorated autoimmune kidney disease in mice. Consistent with these results, the ISR pathway in Trm cells was downregulated in patients with immune-mediated diseases of the kidney and the intestine. Our results identify ISR/eIF2-mediated control of cytokine mRNA translation as an underlying mechanism that restricts Trm cell activity in homeostasis but also promotes rapid response upon local infection or autoimmune reaction.

immunology↗
bioRxiv2024

YamOmics: A comprehensive data resource on yam multi-omics

Yams (Dioscorea spp.) are a highly important class of horticultural crops, serving as a staple food for millions of people in Africa and contributing significantly to food security. They are also widely cultivated in East Asia as medicinal herbs, bringing substantial economic incomes. Diverse omics data play a pivotal role in advancing yam research and breeding. However, these data are often scattered, lacking in systematic organization and analysis, which underscores the need for centralized and comprehensive data management. In view of this, we gathered extensive omics data and developed the Yam Omics Database (YamOmics; https://biotec.njau.edu.cn/yamdb). The database currently offers a vast and diverse range of omics data, covering genomic, transcriptomic and plastomic data from 41 distinct yam species, along with detailed records of genomic variants from [~]1000 germplasms, and gene expression profiles from [~]200 samples. Additionally, the database features thorough annotations, encompassing aspects like genome synteny, ortholog groups, signaling pathways, gene families and protein interactions. To support yam basic biology and breeding research, it is also equipped with a suite of user-friendly online tools, including PCR primer design, CRISPR design, expression analysis, enrichment analysis, and kinship analysis tools.

plant biology↗
bioRxiv2024

Linear-regression-based algorithms can succeed at identifying microbial functional groups despite the nonlinearity of ecological function

Microbial communities play key roles across diverse environments. Predicting their function and dynamics is a key goal of microbial ecology, but detailed microscopic descriptions of these systems can be prohibitively complex. One approach to deal with this complexity is to resort to coarser representations. Several approaches have sought to identify useful groupings of microbial species in a data-driven way. Of these, recent work has claimed some empirical success at de novo discovery of coarse representations predictive of a given function using methods as simple as a linear regression, against multiple groups of species or even a single such group (the EQO approach of Shan et al. [25]). This success seems puzzling, since modeling community function as a linear combination of contributions of individual species appears simplistic. However, the task of identifying a predictive coarsening of an ecosystem is distinct from the task of predicting the function well, and it is conceivable that the former could be accomplished by a simpler methodology than the latter. Here, we use the resource competition framework to design a model where the "correct" grouping to be discovered is well-defined, and use synthetic data to evaluate and compare three regression-based methods, namely, two proposed previously and one we introduce. We find that regression-based methods can recover the groupings even when the function is manifestly nonlinear; that multi-group methods offer an advantage over a single-group EQO; and crucially, that simpler (linear) methods can outperform more complex ones. Author summaryNatural microbial communities are highly complex, making predictive modeling difficult. One appealing approach is to make their description less detailed, rendering modeling more tractable while hopefully still retaining some predictive power. The Tree of Life naturally provides one possible method for building coarser descriptions (instead of thousands of strains, we could think about hundreds of species; or dozens of families). However, it is known that useful descriptions need not be taxonomically coherent, as illustrated, for example, by the so-called functional guilds. This prompted the development of computational methods seeking to propose candidate groupings in a data-driven manner. In this computational study, we examine one class of such methods, recently proposed in the microbial context. Quantitatively testing their performance can be difficult, as the answer they "should" recover is often unknown. Here, we overcome this difficulty by testing these methods on synthetic data from a model where the ground truth is known by construction. Curiously, we demonstrate that simpler approaches, rather than suffering from this simplicity, can in fact be more robust.

ecology↗
bioRxiv2024

Quantifying Interpretation Reproducibility in Vision Transformer Models with TAVAC

The use of deep learning algorithms to extract meaningful diagnostic features from biomedical images holds the promise to improve patient care given the expansion of digital pathology. Among these deep learning models, Vision Transformer (ViT) models have been demonstrated to capture long-range spatial relationships with more robust prediction power for image classification tasks than regular convolutional neural network (CNN) models, and also better model interpretability. Model interpretation is important for understanding and elucidating how a deep learning model makes predictions, especially for developing transparent models for digital pathology. However, like other deep learning algorithms, with limited annotated biomedical imaging datasets, ViT models are prone to poor performance due to overfitting, which can lead to false predictions due to random noise. Overfitting affects model interpretation when predictions are made out of random noise. To address this issue, we introduce a novel metric - Training Attention and Validation Attention Consistency (TAVAC) - for evaluating ViT model degree of overfitting on imaging datasets and quantifying the reproducibility of interpretation. Specifically, the model interpretation is performed by comparing the high-attention regions in the image between training and testing. We test the method on four publicly available image classification datasets and two independent breast cancer histological image datasets. All overfitted models exhibited significantly lower TAVAC scores than the good-fit models. The TAVAC score quantitatively measures the level of generalization of model interpretation on a fine-grained level for small groups of cells in each H&E image, which cannot be provided by traditional performance evaluation metrics like prediction accuracy. Furthermore, the application of TAVAC extends beyond medical diagnostic AI models; it enhances the monitoring of model interpretative reproducibility at pixel-resolution in basic research, to reveal critical spatial patterns and cellular structures essential to understanding biological processes and disease mechanisms. TAVAC sets a new standard for evaluating the performance of deep learning model interpretation and provides a method for determining the significance of high-attention regions detected from the attention map of the biomedical images.

bioinformatics↗
bioRxiv2024

Skeletal Muscle Stem Cells Modulate Niche Function in Duchenne Muscular Dystrophy through YY1-CCL5 Axis

Stem cell activity is known to be tightly regulated by both intrinsic and extrinsic pathways but less is known about whether and how stem cells modulate their niche microenvironment. Adult skeletal muscle stem cells (MuSCs) are indispensable for muscle regeneration and also tightly regulated by macrophages (MPs) and fibro-adipogenic progenitors (FAPs) in the niche. Deregulated MuSC/MP/FAP interactions and the ensuing inflammation and fibrosis are hallmarks of dystrophic muscle. Here in this study we demonstrate that intrinsic deletion of transcription factor YY1 in MuSCs exacerbates dystrophic pathologies by altering the cellular composition and heterogeneity of MPs and FAPs. Further analysis reveals that the YY1 loss induces the expression of immune genes in MuSCs, including Ccl5. Augmented secretion of CCL5 from MuSCs promotes the recruitment of MPs via CCL5/CCR5 mediated crosstalk, which subsequently hinders the apoptosis and clearance of FAPs through elevated TGF{beta}1 accumulation. Maraviroc mediated pharmacological blockade of the CCL5/CCR5 axis effectively mitigates muscle dystrophy and improves muscle performance. Lastly, we further demonstrate that YY1 represses Ccl5 transcription in MuSCs by directly binding to its enhancer thus facilitating promoter-enhancer looping. Altogether, our study has demonstrated the previously unappreciated role of MuSCs in actively shaping their niche microenvironment through secreting immunomodulatory cytokines, and has also provided novel insight into the therapeutic intervention of muscle dystrophy.

cell biology↗
bioRxiv2024

Short-chain fatty acids propionate and butyrate control growth and differentiation linked to cellular metabolism

The short-chain fatty acids (SCFA) propionate and butyrate have beneficial health effects, are produced in large amounts by microbial metabolism and have been identified as unique acyl lysine histone marks. In order to better understand the function of these modifications we used ChIP-seq to map the genome-wide location of four short-chain acyl histone marks H3K18pr, H3K18bu, H4K12pr and H4K12bu in treated and untreated colorectal cancer (CRC) and normal cells, as well as in mouse intestines in vivo. We correlate these marks with open chromatin regions along with gene expression to access the function of the target regions. Our data demonstrate that propionate and butyrate bind and act as promoters of genes involved in growth, differentiation as well as ion transport. We propose a mechanism involving direct modification of specific genomic regions, by SCFA resulting in increased chromatin accessibility, and in case of butyrate, opposing effects on the proliferation of normal versus CRC cells.

genetics↗
bioRxiv2024

Pharmacogenomic discovery of genetically targeted cancer therapies optimized against clinical outcomes

Despite the clinical success of dozens of genetically targeted cancer therapies, the vast majority of patients with tumors caused by loss-of-function (LoF) mutations do not have access to these treatments. This is primarily due to the challenge of developing a drug that treats a disease caused by the absence of a protein target. The success of PARP inhibitors has solidified synthetic lethality (SL) as a means to overcome this obstacle. Recent mapping of SL networks using pooled CRISPR-Cas9 screens is a promising approach for expanding this concept to treating cancers driven by additional LoF drivers. In practice, however, translating signals from cell lines, where these screens are typically conducted, to patient outcomes remains a challenge. We developed a pharmacogemic (PGx) approach called "Clinically Optimized Driver Associated PGx" (CODA-PGx) that accurately predicts genetically targeted therapies with clinical-stage efficacy in specific LoF driver contexts. Using approved targeted therapies and cancer drugs with available real-world evidence and molecular data from hundreds of patients, we discovered and optimized the key screening principles predictive of efficacy and overall patient survival. In addition to establishing basic technical conventions, such as drug concentration and screening kinetics, we found that replicating the driver perturbation in the right context, as well as selecting patients where those drivers are genuine founder mutations, were key to accurate translation. We used CODA-PGX to screen a diverse collection of clinical stage drugs and report dozens of novel LoF genetically targeted opportunities; many validated in xenografts and by real-world evidence. Notable examples include treating STAG2-mutant tumors with Carboplatin, SMARCB1-mutant tumors with Oxaliplatin, and TP53BP1-mutant tumors with Etoposide or Bleomycin. One Sentence SummaryWe identified principles of pharmacogenomic screening that predict clinical efficacy in cancer patients with specific driver mutations.

cancer biology↗
bioRxiv2024

Arf GTPase-activating protein ASAP1 specifically binds to 440-kD ankyrin-B

The 440-kD giant ankyrin-B (gAnkB) exclusively localizes to axons and is essential for axon development. However, proteins that specifically bind to gAnkB but not to other isoforms of ankyrins are poorly understood. Here, we discovered that an Arf GTPase-activating protein ASAP1 and ASAP2 specifically binds to a short and disordered sequence unique to gAnkB. Biochemical studies showed that the SH3 domain of ASAP1 binds to a 12-residue, positively charged peptide fragment from gAnkB. The high-resolution structure of the ASAP1-SH3 domain in complex with the gAnkB peptide revealed the mechanism underlying this non-canonical SH3 domain-mediated target recognition. Further structural and bioinformatic analysis revealed additional previously unknown ASAP1-SH3 binding partners including Clasp1 and Clasp2, both of which are well-known microtubule regulators. Among all known ASAP1-SH3 binders including those identified in the current study, gAnkB has the strongest affinity in binding to ASAP1. Our results suggest that ASAP1 may function together with gAnkB in regulating axonal cytoskeletons.

biophysics↗
bioRxiv2024

De novo multi-mechanism antimicrobial peptide design via multimodal deep learning

Artificial intelligence (AI)-driven discovery of antimicrobial peptides (AMPs) is yet to fully utilise their three-dimensional (3D) structural characteristics, microbial specie-specific antimicrobial activities and mechanisms. Here, we constructed a QLAPD database comprising the sequence, structures and antimicrobial properties of 12,914 AMPs. QLAPD underlies a multimodal, multitask, multilabel, and conditionally controlled AMP discovery (M3-CAD) pipeline, which is proposed for the de novo design of multi-mechanism AMPs to combat multidrug-resistant organisms (MDROs). This pipeline integrates the generation, regression, and classification modules, using a innovative 3D voxel coloring method to capture the nuanced physicochemical context of amino acids, significantly enhancing structural characterizations. QL-AMP-1, discovered by M3-CAD, which possesses four antimicrobial mechanisms, exhibited low toxicity and significant activity against MDROs. The skin wound infection model demonstrates its considerable antimicrobial effects and negligible toxicity. Altogether, integrating 3D features, specie-specific antimicrobial activities and mechanisms enhanced AI-driven AMP discovery, making the M3-CAD pipeline a viable tool for de novo AMP design.

bioengineering↗
bioRxiv2023

Homological landscape of human brain functional sub-circuits

Human whole-brain functional connectivity networks have been shown to exhibit both local/quasilocal (e.g., set of functional sub-circuits induced by node or edge attributes) and non-local (e.g., higher-order functional coordination patterns) properties. Nonetheless, the non-local properties of topological strata induced by local/quasilocal functional sub-circuits have yet to be addressed. To that end, we proposed a homological formalism that enables the quantification of higher-order characteristics of human brain functional sub-circuits. Our results indicated that each homological order uniquely unravels diverse, complementary properties of human brain functional sub-circuits. Noticeably, the H1 homological distance between rest and motor task were observed at both whole-brain and sub-circuit consolidated level which suggested the self-similarity property of human brain functional connectivity unraveled by homological kernel. Furthermore, at the whole-brain level, the rest-task differentiation was found to be most prominent between rest and different tasks at different homological orders: i) Emotion task (H0), ii) Motor task (H1), and iii) Working memory task (H2). At the functional sub-circuit level, the rest-task functional dichotomy of default mode network is found to be mostly prominent at the first and second homological scaffolds. Also at such scale, we found that the limbic network plays a significant role in homological reconfiguration across both task- and subject-domain which sheds light to subsequent investigations on the complex neuro-physiological role of such network. From a wider perspective, our formalism can be applied, beyond brain connectomics, to study non-localized coordination patterns of localized structures stretching across complex network fibers.

neuroscience↗
bioRxiv2023

The ICF2 gene Zbtb24 specifically regulates the differentiation of B1 cells via promoting heme synthesis

Loss-of-function mutations of ZBTB24 cause the Immunodeficiency, Centromeric Instability and Facial Anomalies syndrome 2 (ICF2). ICF2 is a rare autosomal recessive disorder with immunological defects in serum antibodies and circulating memory B cells, indicating an essential role of ZBTB24 in the terminal differentiation of B cells. Here we generated B-cell specific Zbtb24-deficient mice and systemically investigated its role in B cell development and function both in vivo and in vitro. Zbtb24 is dispensable for B cell development & maintenance in naive mice. Surprisingly, B-cell specific deletion of Zbtb24 does not evidently compromise germinal center reactions and the resulting primary & secondary antibody responses induced by T-cell dependent antigens, but significantly inhibits T-cell independent antigen-elicited antibody productions in vivo. At the cellular level, Zbtb24-deficiency specifically impedes the plasma cell differentiation of B1 cells without impairing their survival, activation and proliferation in vitro. Mechanistically, Zbtb24-ablation attenuates heme biosynthesis partially through mTORC1 in B1 cells, and addition of exogenous hemin abrogates the differentiation defects of Zbtb24-null B1 cells. Our study suggests that the defected B1 functions may contribute to recurrent infections in ICF2 patients, and discloses a B1-specific role of Zbtb24 in regulating plasma cell differentiation and antibody production, which is relevant for barrier defenses against invading pathogens.

immunology↗
bioRxiv2023

High-speed AFM reveals fluctuations and dimer splitting of the N-terminal domain of GluA2-γ2

AMPA glutamate receptors (AMPARs) enable rapid excitatory synaptic transmission by localizing to the postsynaptic density of glutamatergic spines. AMPARs possess large extracellular N-terminal domains (NTDs), which participate in AMPAR clustering at synapses. Nevertheless, the dynamics of NTDs and the molecular mechanism governing their synaptic clustering remain elusive. Here, we employed high-speed atomic force microscopy (HS-AFM) to directly visualize the conformational dynamics of NTDs in the GluA2 subunit with TARP {gamma}2 in lipid environments. HS-AFM videos of GluA2-{gamma}2 in the resting and open states revealed fluctuations in NTD dimers. Conversely, in the desensitized state, the two NTD dimers adopted a separated conformation with less fluctuation. Notably, we visualized individual NTD dimers transitioning into monomers. Furthermore, this NTD-dimer splitting resulted in intersubunit exchange between NTD dimers and an increased number of binding sites with the synaptic protein neuronal pentraxin 1. Therefore, our findings illuminate the significance of NTD dynamics in the synaptic clustering of AMPARs.

neuroscience↗
bioRxiv2023

Divergence in herbivore resistance during the invasion of a global plant invader

O_LISuccessful plant invasions are often explained with adaptation to novel environments. However, invasive species often occupy broad niches within their native and introduced ranges, and a true understanding of microevolution during invasion therefore requires broad sampling of ranges, ideally with a knowledge of introduction history. C_LIO_LIWe tested for genetic differentiation in herbivore resistance among 128 introduced (Europe, North America) and native (China, Japan) populations of the invasive Japanese knotweed (Reynoutria japonica) in two common gardens in the native range. C_LIO_LIIn both common gardens we found that resistance traits of introduced populations differed from most Chinese native populations, but not from populations in Japan, the putative sources of introduction. Compared to Chinese populations, introduced European populations had thicker leaves with a lower C:N ratio but higher flavonoids contents. In the native range, variation in herbivore resistance was much more strongly associated with climate of origin than in introduced populations. C_LIO_LIOur results support the idea that founder effects played a key role in the invasion of knotweed into Europe and North America, with introduction of particular resistance phenotypes from Japan. Our study also demonstrates how knowledge of introduction history can avoid drawing wrong conclusions from observed biogeographic divergence. C_LI

ecology↗