Biology subjects

Zheng, Y.

Publications and source records attributed to Zheng, Y..

At least 235 records · Page 13Linked to original sources

bioRxiv2024

Aberrant homeodomain-DNA cooperative dimerization underlies distinct developmental defects in two dominant CRX retinopathy models

Paired-class homeodomain transcription factors (HD TFs) play essential roles in vertebrate development, and their mutations are linked to human diseases. One unique feature of paired-class HD is cooperative dimerization on specific palindrome DNA sequences. Yet, the functional significance of HD cooperative dimerization in animal development and its dysregulation in diseases remain elusive. Using the retinal TF Cone-rod Homeobox (CRX) as a model, we have studied how blindness-causing mutations in the paired HD, p.E80A and p.K88N, alter CRXs cooperative dimerization, lead to gene misexpression and photoreceptor developmental deficits in dominant manners. CRXE80A maintains binding at monomeric WT CRX motifs but is deficient in cooperative binding at dimeric motifs. CRXE80As cooperativity defect impacts the exponential increase of photoreceptor gene expression in terminal differentiation and produces immature, non-functional photoreceptors in the CrxE80A retinas. CRXK88N is highly cooperative and localizes to ectopic genomic sites with strong enrichment of dimeric HD motifs. CRXK88Ns altered biochemical properties disrupt CRXs ability to direct dynamic chromatin remodeling during development to activate photoreceptor differentiation programs and silence progenitor programs. Our study here provides in vitro and in vivo molecular evidence that paired-class HD cooperative dimerization regulates neuronal development and dysregulation of cooperative binding contributes to severe dominant blinding retinopathies.

genetics↗

bioRxiv2024

Engineered Migrasomes: A Robust, Thermally Stable Vaccination Platform

The increasing ability of pathogens and tumor cells to evade immune detection underscores the urgent need for novel vaccine platforms leveraging diverse biological mechanisms. Additionally, logistical challenges associated with cold-chain transportation significantly limit vaccine accessibility, especially in resource-limited regions. Recently, we identified migrasomes, specialized organelles generated during cell migration, which are inherently stable and enriched with immune-modulating molecules. To address the low yield of natural migrasomes, we engineered migrasome-like vesicles (eMigrasomes) using hypotonic shock combined with cytoskeletal disruption to enhance vesicle formation. The biogenesis of eMigrasomes relies on the core migrasome machinery, faithfully recapitulating the biophysical attributes of native migrasomes while significantly improving production efficiency. We demonstrate that eMigrasomes loaded with a model antigen elicit potent antibody responses and maintain structural integrity and immunogenic potential at room temperature. Furthermore, eMigrasomes displaying the SARS-CoV-2 Spike protein induce robust humoral immune responses, providing effective protection against viral infection. Our findings highlight the potential of utilizing migrasome biology and hypotonic shock-driven vesicle generation as an innovative, stable, and broadly accessible vaccine platform.

cell biology↗

bioRxiv2024

Uncovering disease-related multicellular pathway modules on large-scale single-cell transcriptomes with scPAFA

Pathway analysis is a crucial analytical phase in disease research on single-cell RNA sequencing (scRNA-seq) data, offering biological interpretations based on prior knowledge. However, currently available tools for generating cell-level pathway activity scores (PAS) exhibit computational inefficacy in large-scale scRNA-seq datasets. Besides, disease-related pathways are commonly identified by cross-condition comparisons in each cell type, neglecting the potential multicellular patterns. Here, we present single-cell pathway activity factor analysis (scPAFA), a Python library designed for large-scale single-cell dataset allowing rapid PAS computation and uncovering biologically interpretable disease-related multicellular pathway modules, which are low-dimensional representations of disease-related PAS variance in multiple cell types. Application on colorectal cancer (CRC) dataset with 371,223 cells and large-scale lupus atlas over 1.2 million cells demonstrated that scPAFA can achieve > 33-fold decreases in runtime of PAS computation and further identified reliable and interpretable multicellular pathway modules that capture the transcriptomic features of CRC tumor status and transcriptional abnormalities in lupus patients, respectively.

bioinformatics↗

bioRxiv2024

The heritability and structural correlates of brain entropy

Brain entropy (BEN) quantifies the temporal complexity of spontaneous neural activity, which has been increasingly recognized as providing important insights into cognitive functions and psychiatric disorders. However, its heritability and structural underpinnings are not well understood. Here, we utilize sample entropy to calculate BEN in healthy young adults using resting-state fMRI from the Human Connectome Project. We show that BEN is significantly heritable in broad brain regions. Heritability estimates exhibit regional variability, with lower heritability in the limbic and subcortical networks than in other networks. We further relate BEN to structural features including surface area (SA), cortical myelination (CM), cortical thickness (CT), and subcortical volumes (SV). We find that BEN is negatively correlated with SA in most cortical regions, but is positively correlated with CM in the prefrontal cortex, lateral temporal lobe, precuneus, lateral parietal cortex, and cingulate cortex. Only a few cortical regions show significant correlations between BEN and CT. By decomposing correlations into genetic and environmental components, we observe that most of BEN-SA correlations are associated with shared genetic and environmental effects. BEN-CM correlations are mainly attributed to shared environmental effects. BEN-CT correlations are partly related to shared environmental effects. We find no significant associations between BEN and SV. Collectively, our work establishes the genetic basis and structural correlates of resting-state fMRI-based BEN, supporting its potential application as an endophenotype for psychiatric disorders.

neuroscience↗

bioRxiv2024

Development of an orally bioavailable mSWI/SNF ATPase degrader and acquired mechanisms of resistance in prostate cancer

Mammalian switch/sucrose non-fermentable (mSWI/SNF) ATPase degraders have been shown to be effective in enhancer-driven cancers by functioning to impede oncogenic transcription factor chromatin accessibility. Here, we developed AU-24118, a first-in-class, orally bioavailable proteolysis targeting chimera (PROTAC) degrader of mSWI/SNF ATPases (SMARCA2 and SMARCA4) and PBRM1. AU-24118 demonstrated tumor regression in a model of castration-resistant prostate cancer (CRPC) which was further enhanced with combination enzalutamide treatment, a standard of care androgen receptor (AR) antagonist used in CRPC patients. Importantly, AU-24118 exhibited favorable pharmacokinetic profiles in preclinical analyses in mice and rats, and further toxicity testing in mice showed a favorable safety profile. As acquired resistance is common with targeted cancer therapeutics, experiments were designed to explore potential mechanisms of resistance that may arise with long-term mSWI/SNF ATPase PROTAC treatment. Prostate cancer cell lines exposed to long-term treatment with high doses of a mSWI/SNF ATPase degrader developed SMARCA4 bromodomain mutations and ABCB1 overexpression as acquired mechanisms of resistance. Intriguingly, while SMARCA4 mutations provided specific resistance to mSWI/SNF degraders, ABCB1 overexpression provided broader resistance to other potent PROTAC degraders targeting bromodomain-containing protein 4 (BRD4) and AR. The ABCB1 inhibitor, zosuquidar, reversed resistance to all three PROTAC degraders tested. Combined, these findings position mSWI/SNF degraders for clinical translation for patients with enhancer-driven cancers and define strategies to overcome resistance mechanisms that may arise. Significance StatementThe mSWI/SNF complex is a promising therapeutic target for enhancer-driven cancers. PROTACs, which enable the targeting of "undruggable" proteins, often face the challenge of achieving oral bioavailability. Here, we present AU-24118, a first-in-class, orally bioavailable mSWI/SNF ATPase dual degrader with remarkable efficacy in in vitro and in vivo models. Additionally, our study describes two distinct mechanisms of resistance to PROTAC degraders, providing crucial insights into potential challenges facing their clinical application. These findings are critical for advancing PROTAC-based therapies to clinical settings as targeted therapies for cancers.

cancer biology↗

bioRxiv2024

PIKfyve controls dendritic cell function and tumor immunity

The modern armamentarium for cancer treatment includes immunotherapy and targeted therapy, such as protein kinase inhibitors. However, the mechanisms that allow cancer-targeting drugs to effectively mobilize dendritic cells (DCs) and affect immunotherapy are poorly understood. Here, we report that among shared gene targets of clinically relevant protein kinase inhibitors, high PIKFYVE expression was least predictive of complete response in patients who received immune checkpoint blockade (ICB). In immune cells, high PIKFYVE expression in DCs was associated with worse response to ICB. Genetic and pharmacological studies demonstrated that PIKfyve ablation enhanced DC function via selectively altering the alternate/non-canonical NF-{kappa}B pathway. Both loss of Pikfyve in DCs and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively controls DCs, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.

cancer biology↗

bioRxiv2024

A comprehensive personal omics clinical interpreter based on genomic and transcriptomic profiles

Advances in precision medicine rely on the accurate identification and analysis of molecular alterations for personalized diagnostic, prognostic, and therapeutic decision-making. A critical obstacle is the integration of heterogeneous interpretations of clinically actionable alterations from various knowledgebases. Here, we present the Personal Omics Interpreter (POI), a web-based application engineered to aggregate and interpret therapeutic options, including targeted, immunological, and chemotherapeutic agents, by leveraging personal genomic and transcriptomic profiles. POI employs the Precision Medicine Knowledgebase (PreMedKB), an updated harmonized resource we previously reported, to annotate the clinically actionable somatic variants. It further incorporates a predictive algorithm to broaden therapeutic options according to established gene-gene interactions and offers insights into phenotypic responses of chemotherapeutic agents through phasing germline diplotypes. Validated against three cohort datasets encompassing over 22,000 cancer patients, POI demonstrates consistently high matching rates (94.7 [~] 95.6%) between patients and suggested therapies, highlighting its potential in supporting precision-driven informed treatment strategies.

genomics↗

bioRxiv2024

Construction and Application of a Technical Platform for Determining Cell Cycle- and Autophagy-Associated Cellular Uptake of Lipid-Based Nanoparticles

Cellular accumulation of biomedical nanoparticles could be affected by cellular biological properties. However, little is known about the influence of cell cycle and autophagy on nanoparticle accumulation. Whats even more tough is that several long-lasting methodological barriers have hampered the experimental performance and restricted related research progress. Herein, a multi-functional platform was constructed for simultaneously overcoming existing obstacles by integrating several technical approaches, particularly mitotic shake-off, for thorough cell cycle phase separation. Strikingly, application of this platform revealed that G2-phase and M-phase cells, two cell populations previously muddled up together as G2/M-phase cells, respectively exhibited the maximum and minimum accumulation of lipid-based nanoparticles. Moreover, although further verification is needed, we have provided a novel line of evidence for enhanced nanoparticle accumulation by autophagy blockade. Besides providing a technical solution, this study discovered characteristic cell cycle- and autophagy-associated nanoparticle accumulations that may offer new insights for optimization and application of nanomedicines.

cell biology↗

bioRxiv2024

Marsilea: An intuitive generalized visualization paradigm for complex datasets

Contemporary data visualization is challenged by the growing complexity and size of datasets, often comprising numerous interrelated features. Traditional visualization methods struggle to capture these complex relationships fully or are specialized to a domain requiring familiarity with multiple visualization tools. We introduce a novel and intuitive general visualization paradigm, termed "cross-layout visualization", which integrates multiple plot types in a cross-like structure. This paradigm allows for a central main plot surrounded by secondary plots, each capable of layering additional features for enhanced context and understanding. To operationalize this paradigm, we present "Marsilea", a Python library designed for creating complex visualizations with ease. Marsilea is notable for its modularity, diverse plot types, compatibility with various data formats, and is available in a coding-free web-based interface for users of all experience levels. We showcase its versatility and broad applicability by re-creating existing visualizations and creating novel visualizations that include elements such as heatmaps, sequence motifs, and set intersections that are typically beyond the scope of existing general visualization tools. The cross-layout paradigm, exemplified by Marsilea, offers a flexible, customizable, and intuitive approach to complex data visualization, promising to enhance data analysis across scientific domains.

bioinformatics↗

bioRxiv2024

Photo-Uncaging Triggers on Self-Blinking to Control Single-Molecule Fluorescence Kinetics for Super-Resolution Imaging

Super-resolution imaging in a single-molecule localization approach has transformed the bulk fluorescence requirements to a single-molecule level, raising a revolution in the fluorophore engineering. Yet, it is a challenge to structurally devise fluorophores manipulating the single-molecule blinking kinetics. In this pursuit, we have developed a new strategy by innovatively integrating the photoactivatable nitroso-caging strategy into self-blinking sulfonamide, to forming a nitroso-caged sulfonamide rhodamine (NOSR). Our fluorophore demonstrated controllable self-blinking events upon photo-triggered uncaging release. This exceptional blink kinetics improved integrity in super-resolution imaging microtubules compared to self-blinking analogues. With the aid of paramount single-molecule fluorescence kinetics, we successfully reconstructed the axial morphology of mitochondrial outer membranes. We foresee that our synthetic approach of photoactivation and self-blinking would set a new avenue for devising rhodamines for super-resolution imaging. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/580074v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@18d51d5org.highwire.dtl.DTLVardef@f7a1cdorg.highwire.dtl.DTLVardef@19fcc7dorg.highwire.dtl.DTLVardef@2a5bcb_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Neurotensin-Neurotensin Receptor 2 signaling in adipocytes regulates food intake through ceramide metabolism

Neurotensin (NTS) is a secretory peptide produced by the lymphatic endothelial cells (LEC). Our previous study revealed that NTS suppressed the activity of brown adipose tissue via the interactions with NTSR2. In the current study, we found that the depletion of Ntsr2 in the white adipocytes upregulated food intake, while the local treatment of NTS suppressed the food intake. Mechanistic study revealed that the suppression of NTS-NTSR2 signaling enhanced the phosphorylation of ceramide synthetase 2 (CerS2), increased the abundance of its products ceramide C20-C24 and downregulated the production of GDF15 in the white adipose tissues, which was responsible for the elevation of food intake. With four populations of different age and ethnic background, we discovered a potential causal and positive correlation between ceramide C20-24 and food intake in human. Our study identified that NTS-NTSR2 signaling can perform the neurological regulation via controlling the production of ceramide in the white adipocytes.

physiology↗

bioRxiv2024

Neurotrophic factor Neuritin modulates T cell electrical and metabolic state for the balance of tolerance and immunity

The adaptive T cell response is accompanied by continuous rewiring of the T cells electric and metabolic state. Ion channels and nutrient transporters integrate bioelectric and biochemical signals from the environment, setting cellular electric and metabolic states. Divergent electric and metabolic states contribute to T cell immunity or tolerance. Here, we report that neuritin (Nrn1) contributes to tolerance development by modulating regulatory and effector T cell function. Nrn1 expression in regulatory T cells promotes its expansion and suppression function, while expression in the T effector cell dampens its inflammatory response. Nrn1 deficiency causes dysregulation of ion channel and nutrient transporter expression in Treg and effector T cells, resulting in divergent metabolic outcomes and impacting autoimmune disease progression and recovery. These findings identify a novel immune function of the neurotrophic factor Nrn1 in regulating the T cell metabolic state in a cell context-dependent manner and modulating the outcome of an immune response.

immunology↗

bioRxiv2024

Targeting the mSWI/SNF Complex in POU2F-POU2AF Transcription Factor-Driven Malignancies

The POU2F3-POU2AF2/3 (OCA-T1/2) transcription factor complex is the master regulator of the tuft cell lineage and tuft cell-like small cell lung cancer (SCLC). Here, we found that the POU2F3 molecular subtype of SCLC (SCLC-P) exhibits an exquisite dependence on the activity of the mammalian switch/sucrose non-fermentable (mSWI/SNF) chromatin remodeling complex. SCLC-P cell lines were sensitive to nanomolar levels of a mSWI/SNF ATPase proteolysis targeting chimera (PROTAC) degrader when compared to other molecular subtypes of SCLC. POU2F3 and its cofactors were found to interact with components of the mSWI/SNF complex. The POU2F3 transcription factor complex was evicted from chromatin upon mSWI/SNF ATPase degradation, leading to attenuation of downstream oncogenic signaling in SCLC-P cells. A novel, orally bioavailable mSWI/SNF ATPase PROTAC degrader, AU-24118, demonstrated preferential efficacy in the SCLC-P relative to the SCLC-A subtype and significantly decreased tumor growth in preclinical models. AU-24118 did not alter normal tuft cell numbers in lung or colon, nor did it exhibit toxicity in mice. B cell malignancies which displayed a dependency on the POU2F1/2 cofactor, POU2AF1 (OCA-B), were also remarkably sensitive to mSWI/SNF ATPase degradation. Mechanistically, mSWI/SNF ATPase degrader treatment in multiple myeloma cells compacted chromatin, dislodged POU2AF1 and IRF4, and decreased IRF4 signaling. In a POU2AF1-dependent, disseminated murine model of multiple myeloma, AU-24118 enhanced survival compared to pomalidomide, an approved treatment for multiple myeloma. Taken together, our studies suggest that POU2F-POU2AF-driven malignancies have an intrinsic dependence on the mSWI/SNF complex, representing a therapeutic vulnerability.

cancer biology↗

bioRxiv2024

Bypassing PELO-mediated ATPase activation of NLR is a common pathogenic cause of NLR-associated autoinflammatory diseases

Nucleotide-binding and oligomerization domain (NOD)-like receptors (NLRs) constitute the largest family of pattern recognition receptors. These receptors are master regulators of innate immunity. Recently, PELO-driven ATPase activation of NLRs was demonstrated as a critical step in NLR activation. Linkage studies in human with various inherited autoinflammatory conditions have revealed an extensive array of mutations and polymorphisms within NLRs. However, the precise mechanisms by which genetic variations in NLR genes contribute to disease onset remain largely elusive. Here we comprehensively analyze dozens of naturally occurring mutations across multiple human NLRs, and demonstrate that NLRs harboring pathogenic mutations in their NACHT domain--not those with non-pathogenic variants--exhibit spontaneous PELO-independent ATPase activation. This aberrant activation triggers corresponding NLR to mediate inflammatory responses. Thus, bypassing the PELO-checkpoint for ATPase activation is a major disease-causing mechanism underlying NLR mutations. Furthermore, quantifying this aberrant ATPase activation could serve as an assessment tool for classifying the pathogenesis of NLR-associated diseases.

immunology↗

bioRxiv2024

MATES: A Deep Learning-Based Model for Locus-specific Quantification of Transposable Elements in Single Cell

Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either best-mapped or random-mapped locations and categorize them at subfamily levels, overlooking the biological necessity for accurate, locus-specific TE quantification. Moreover, these existing methods are primarily designed for and focused on transcriptomics data, which restricts their adaptability to single-cell data of other modalities. To address these challenges, here we introduce MATES, a deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. When applied to diverse single-cell omics datasets, MATES shows improved performance over existing methods, enhancing the accuracy of TE quantification and aiding in the identification of marker TEs for identified cell populations. This development facilitates the exploration of single-cell heterogeneity and gene regulation through the lens of TEs, offering an effective transposon quantification tool for the single-cell genomics community.

bioinformatics↗

bioRxiv2024

HortGenome Search Engine, a universal genomic search engine for horticultural crops

Horticultural crops comprising fruit, vegetable, ornamental, beverage, medicinal and aromatic plants play essential roles in food security and human health, as well as landscaping. With the advances of sequencing technologies, genomes for hundreds of horticultural crops have been deciphered in recent years, providing a basis for understanding gene functions and regulatory networks and for the improvement of horticultural crops. However, these valuable genomic data are scattered in warehouses with various complex searching and displaying strategies, which increases learning and usage costs and makes comparative and functional genomic analyses across different horticultural crops very challenging. To this end, we have developed a lightweight universal search engine, HortGenome Search Engine (HSE; http://hort.moilab.net), which allows querying genes, functional annotations, protein domains, homologs, and other gene-related functional information of more than 400 horticultural crops. In addition, four commonly used tools, including BLAST, Batch Query, Enrichment analysis, and Synteny Viewer, have been developed for efficient mining and analysis of these genomic data.

bioinformatics↗

bioRxiv2023

Toward Best Practice in Identifying Subtle Differential Expression with RNA-seq: A Real-World Multi-Center Benchmarking Study Using Quartet and MAQC Reference Materials

Translating RNA-seq into clinical diagnostics requires ensuring the reliability of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. Moreover, cross-laboratory reproducibility and consistency under diverse experimental and bioinformatics workflows urgently need to be addressed. As part of the Quartet project, we presented a comprehensive RNA-seq benchmarking study utilizing Quartet and MAQC RNA reference samples spiked with ERCC controls in 45 independent laboratories, each employing their in-house RNA-seq workflows. We assessed the data quality, accuracy and reproducibility of gene expression and differential gene expression and compared over 40 experimental processes and 140 combined differential analysis pipelines based on multiple ground truths. Here we show that real-world RNA-seq exhibited greater inter-laboratory variations when detecting subtle differential expressions between Quartet samples. Experimental factors including mRNA enrichment methods and strandedness, and each bioinformatics step, particularly normalization, emerged as primary sources of variations in gene expression and have a more pronounced impact on the subtle differential expression measurement. We underscored the pivotal role of experimental execution over the choice of experimental protocols, the importance of strategies for filtering low-expression genes, and optimal gene annotation and analysis tools. In summary, this study provided best practice recommendations for the development, optimization, and quality control of RNA-seq for clinical diagnostic purposes.

genomics↗

bioRxiv2023

Linking Structure and Function: Image-Based Virtual Populations of the Retinal Vasculature

PurposeThis study explores the relationship between microvascular parameters as delineated by optical coherence tomography angiography (OCTA) and retinal perfusion. We introduce a versatile framework to examine the interplay between the retinal vasculature structure and function, generating virtual vasculatures from central retinal vessels to macular capillaries. Alongside this, we develop a haemodynamics model which tests the associations between vascular morphology and retinal perfusion. MethodsThe generation of the vasculature is based on the distribution of four clinical parameters pertaining to the dimension and blood pressure of the central retinal vessels, constructive constrained optimisation and Voronoi diagram. Arterial and venous trees are generated in the temporal retina and connected through three layers of capillaries at different depths in the macula. The correlations between total retinal blood flow and macular flow fraction and vascular morphology are derived as Spearman rank coefficients and uncertainty from input parameters is quantified. ResultsA virtual cohort of 200 healthy vasculatures were generated. Mean and standard deviation for retinal blood flow and macular flow ratio were 19.15 {+/-} 7.34 L/min and 4.52 {+/-} 1.19 %. Retinal blood flow was correlated with vessel area density, vessel diameter index, fractal dimension and vessel calibre index. The macular flow fraction was not correlated with any morphological metrics. ConclusionsThe proposed framework is able to reproduce vascular networks in the macula that are morphologically and functionally similar to real vasculature. The framework provides quantitative insights into how macular perfusion can be affected by changes in vascular morphology delineated on OCTA.

physiology↗