Biology subjects

Zhuang, P.

Publications and source records attributed to Zhuang, P..

12 recordsLinked to original sources

bioRxiv2024

PRLX-93936 and BMS-214662 are cytotoxic molecular glues that leverage TRIM21 to degrade nucleoporins

Although molecular glues have emerged as innovative tools within the field of chemically induced proximity, approaches for their discovery remain limited. Here we report a phenotypic screening approach in which small molecules whose cytotoxic mechanisms require ubiquitination show gain of viability following pharmacological inhibition of the E1 enzyme UAE. This approach revealed two previously clinically-evaluated cytotoxins of unknown mechanism, PRLX-93936 and BMS-214662, as molecular glues that directly target the E3 ubiquitin ligase TRIM21. These molecules induce TRIM21-mediated proteasomal degradation of multiple nucleoporin proteins, leading to inhibition of nuclear export and ultimately cell death. Loss of nucleoporins and nuclear export accounts for past observations in which BMS-214662 led to disrupted subcellular protein localization. Furthermore, the cytotoxicity of these agents correlates strongly with TRIM21 expression, suggesting clinical re-evaluation of these agents in patients with TRIM21-high cancers. Additionally, relative to recently-reported TRIM21-targeting glues, these two scaffolds display high cellular potency, creating new opportunities for targeted protein degradation via the design of additional glues and TRIMTACs.

pharmacology and toxicology↗

bioRxiv2024

Blood-tumor barrier organoids recapitulate glioblastoma microenvironment and enable high-throughput modeling of therapeutic delivery

The blood-brain barrier (BBB) is a highly specialized system that is critical for regulating transport between the blood and the central nervous system. In brain tumors, the vasculature system is compromised, and is referred to as the blood-tumor barrier (BTB). The ability to precisely model the unique physiological properties of the BTB is essential to decipher its role in tumor pathophysiology and for the rational design of efficacious therapeutics. Here, we introduce a robust and high-throughput in vitro 3D human BTB organoid model that recapitulates various key features of the BTB observed in vivo and in clinical GBM samples. The organoids are composed of patient-derived glioblastoma stem cells (GSCs), human brain endothelial cells (EC), astrocytes and pericytes, which are formed through self-assembly. Transcriptomic and functional analyses reveal that the GSCs in the BTB organoids exhibit enhanced level of stemness, mesenchymal signature, invasiveness and angiogenesis, and this is further confirmed in in vivo studies. We demonstrate the ability of the BTB organoids to model therapeutic delivery and drug efficacy on brain tumor cells. Collectively, our findings show that the BTB organoid model has broad utility as a clinically representative system for studying the BTB and evaluating brain tumor therapies.

bioengineering↗

bioRxiv2024

PACT prevents aberrant activation of PKR by endogenous dsRNA without sequestration

The innate immune sensor PKR for double-stranded RNA (dsRNA) is critical for antiviral defense, but its aberrant activation by cellular dsRNA is linked to various diseases. The dsRNA-binding protein PACT plays a critical yet controversial role in the PKR pathway. We demonstrate that PACT is a direct and specific suppressor of PKR against endogenous dsRNA ligands like inverted-repeat Alu RNAs, which robustly activate PKR in the absence of PACT. PACT-mediated inhibition does not involve competition for dsRNA binding. Instead, PACT impairs PKRs ability to scan along dsRNA--a process necessary for PKR molecules to encounter and autophoshorylate each other for activation. By scanning along dsRNA and directly interacting with PKR, PACT restricts PKRs movement on dsRNA, reducing the likelihood of PKR molecular collisions and subsequent autophosphorylation, effectively inhibiting PKR without sequestering dsRNA. Consequently, PKR inhibition is more robust with longer and less abundant dsRNA, and minimal with abundant or short dsRNA. Thus, PACT functions to adjust the PKR activation threshold for long endogenous dsRNA without altering its inherent activity, revealing new mechanisms for establishing self-tolerance.

biochemistry↗

bioRxiv2023

XRN1 deletion induces PKR-dependent cell lethality in interferon-activated cancer cells

Emerging data suggest that induction of viral mimicry responses through activation of double-stranded RNA (dsRNA) sensors in cancer cells is a promising therapeutic strategy. One approach to induce viral mimicry is to target molecular regulators of dsRNA sensing pathways. Here, we show that the exoribonuclease XRN1 is a negative regulator of the dsRNA sensor protein kinase R (PKR) in cancer cells with high interferon-stimulated gene (ISG) expression. XRN1 deletion causes PKR activation and consequent cancer cell lethality. Disruption of interferon signaling with the JAK1/2 inhibitor ruxolitinib can decrease cellular PKR levels and rescue sensitivity to XRN1 deletion. Conversely, interferon-{beta} stimulation can increase PKR levels and induce sensitivity to XRN1 inactivation. Lastly, XRN1 deletion causes accumulation of endogenous complementary sense/anti-sense RNAs, which may represent candidate PKR ligands. Our data demonstrate how XRN1 regulates PKR and nominate XRN1 as a potential therapeutic target in cancer cells with an activated interferon cell state.

cancer biology↗

bioRxiv2023

Theranostic Bottle-Brush Polymers Tailored for Universal Solid-Tumour Targeting

Nanomedicines involving nanotechnologies and engineering of nanomaterials for medicines have shown great promise in diagnosis and treatment of diseases including cancers. A major hurdle that limits the successful clinical translation of nanomedicines, however, is how to overcome the cascaded biological barriers and improve the delivery efficacy towards the disease sites and minimize the toxicity against healthy tissues and cells. Here, we report a type of bottle-brush-like polymers systematically optimized in their chemical structures, sizes, and surface charges that lead to their outstanding pharmacokinetics and tumour-targeting performances in a variety of both subcutaneous and orthotopic tumour models. The potential mechanism has been studied by revealing the structure-activity relationship of these polymers in overcoming the biological barriers, including their avoidance by the immune system and deep tumour infiltration. Our study may offer insight for a rational design of highly efficient delivery platform of polymeric nanomedicines that could effectively overcome the cascaded biological barriers and thus lead to high tumour-targeting efficacy and low toxicity.

bioengineering↗

bioRxiv2022

Silicone Oil-Induced Glaucomatous Neurodegeneration in Rhesus Macaques

Previously, we developed a simple procedure of intracameral injection of silicone oil (SO) into mouse eyes and established the mouse SOHU (SO-induced ocular hypertension under-detected) glaucoma model with reversible intraocular pressure (IOP) elevation and significant glaucomatous neurodegeneration. Because the anatomy of the non-human primate (NHP) visual system closely resembles that of humans, it is the most likely to predict human responses to diseases and therapies. Here we replicated the SOHU glaucoma model in rhesus macaque monkeys. All six animals that we tested showed significant retinal ganglion cell (RGC) death, optic nerve (ON) degeneration, and visual functional deficits at both 3 and 6 months. In contrast to the mouse SOHU model, IOP changed dynamically in these animals, probably due to individual differences in ciliary body tolerance capability. This acute NHP glaucoma model closely recapitulates the major features of glaucomatous neurodegeneration in humans, and is therefore suitable for studying the pathology of primate RGC/ON, assessing experimental therapies for neuroprotection and regeneration, and therefore for translating relevant findings into novel and effective treatments for patients with glaucoma and other neurodegenerations.

neuroscience↗

bioRxiv2022

ViPal: A Framework for Virulence Prediction of Influenza Viruses with Prior Viral Knowledge Using Genomic Sequences

Influenza viruses pose significant threats to public health and cause enormous economic loss every year. Previous work has revealed the viral factors that influence the virulence of influenza viruses. However, taking prior viral knowledge represented by heterogeneous categorical and discrete information into account is scarce in the existing work. How to make full use of the preceding domain knowledge into virulence study is challenging but beneficial. This paper proposes a general framework named ViPal for virulence prediction that incorporates discrete prior viral mutation and reassortment information based on all eight influenza segments. The posterior regularization technique is leveraged to transform prior viral knowledge to constraint features and integrated into the machine learning models. Experimental results on influenza genomic datasets validate that our proposed framework can improve virulence prediction performance over baselines. The comparison between ViPal and other existing methods shows the computational efficiency of our framework with superior performance. Moreover, the interpretable analysis through SHAP identifies the scores of constraint features contributing to the prediction. We hope this framework could provide assistance for the accurate detection of influenza virulence and facilitate flu surveillance.

bioinformatics↗

bioRxiv2020

Regulation of retinal amacrine cell generation by miR-216b and Foxn3

The mammalian retina contains a complex mixture of different types of neurons. We find that the microRNA miR-216b is preferentially expressed in postmitotic retinal amacrine cells in the mouse retina, and expression of miR-216a/b and miR-217 in the retina depend in part on Ptf1a, a transcription factor required for amacrine cell differentiation. Surprisingly, ectopic expression of miR-216b, or the related miR-216a, can direct the formation of additional amacrine cells in the developing retina. In addition, we observe the loss of bipolar neurons in the retina after miR-216b expression. We identify the mRNA for the transcriptional regulator Foxn3 as a retinal target of miR-216b by Argonaute PAR-CLIP and reporter analysis. Inhibition of Foxn3 in the postnatal developing retina by RNAi also increases the formation of amacrine cells and reduces bipolar cell formation, while overexpression of Foxn3 inhibits amacrine cell formation prior to the expression of Ptf1a. Disruption of Foxn3 by CRISPR in embryonic retinal explants also reduces amacrine cell formation. Co-expression of Foxn3 can partially reverse the effects of ectopic miR-216b on retinal cell type formation. Our results identify Foxn3 as a novel regulator of interneuron formation in the developing retina and suggest that miR-216b likely regulates expression of Foxn3 and other genes in amacrine cells.

neuroscience↗

bioRxiv2020

VirPreNet: A weighted ensemble convolutional neural network for the virulence prediction of influenza A virus using all 8 segments

MotivationInfluenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics. The evolution of influenza viruses remains to be the main obstacle in the effectiveness of antiviral treatments due to rapid mutations. Previous work has been investigated to reveal the determinants of virulence of the influenza A virus. To further facilitate flu surveillance, explicit detection of influenza virulence is crucial to protect public health from potential future pandemics. ResultsIn this paper, we propose a weighted ensemble convolutional neural network for the virulence prediction of influenza A viruses named VirPreNet that uses all 8 segments. Firstly, mouse lethal dose 50 is exerted to label the virulence of infections into two classes, namely avirulent and virulent. A numerical representation of amino acids named ProtVec is applied to the 8-segments in a distributed manner to encode the biological sequences. After splittings and embeddings of influenza strains, the ensemble convolutional neural network is constructed as the base model on the influenza dataset of each segment, which serves as the VirPreNets main part. Followed by a linear layer, the initial predictive outcomes are integrated and assigned with different weights for the final prediction. The experimental results on the collected influenza dataset indicate that VirPreNet achieves state-of-the-art performance combining ProtVec with our proposed architecture. It outperforms baseline methods on the independent testing data. Moreover, our proposed model reveals the importance of PB2 and HA segments on the virulence prediction. We believe that our model may provide new insights into the investigation of influenza virulence. Contactyinr0002@e.ntu.edu.sg Availability and ImplementationCodes and data to generate the VirPreNet are publicly available at https://github.com/Rayin-saber/VirPreNet

bioinformatics↗

bioRxiv2020

IAV-CNN: a 2D convolutional neural network model to predict antigenic variants of influenza A virus

The rapid evolution of influenza viruses constantly leads to the emergence of novel influenza strains that are capable of escaping from population immunity. The timely determination of antigenic variants is critical to vaccine design. Empirical experimental methods like hemagglutination inhibition (HI) assays are time-consuming and labor-intensive, requiring live viruses. Recently, many computational models have been developed to predict the antigenic variants without considerations of explicitly modeling the interdependencies between the channels of feature maps. Moreover, the influenza sequences consisting of similar distribution of residues will have high degrees of similarity and will affect the prediction outcome. Consequently, it is challenging but vital to determine the importance of different residue sites and enhance the predictive performance of influenza antigenicity. We have proposed a 2D convolutional neural network (CNN) model to infer influenza antigenic variants (IAV-CNN). Specifically, we introduce a new distributed representation of amino acids, named ProtVec that can be applied to a variety of downstream proteomic machine learning tasks. After splittings and embeddings of influenza strains, a 2D squeeze-and-excitation CNN architecture is constructed that enables networks to focus on informative residue features by fusing both spatial and channel-wise information with local receptive fields at each layer. Experimental results on three influenza datasets show IAV-CNN achieves state-of-the-art performance combing the new distributed representation with our proposed architecture. It outperforms both traditional machine algorithms with the same feature representations and the majority of existing models in the independent test data. Therefore we believe that our model can be served as a reliable and robust tool for the prediction of antigenic variants.

bioinformatics↗

bioRxiv2019

Silicone oil-induced ocular hypertension in mouse models glaucomatous neurodegeneration and neuroprotection

Understanding the molecular mechanism of glaucoma and development of neuroprotectants are significantly hindered by the lack of a reliable animal model that accurately recapitulates human glaucoma. Here we sought to develop a mouse model for the secondary glaucoma that is often observed in humans after silicone oil (SO) blocks the pupil or migrates into the anterior chamber following vitreoretinal surgery. We observed similar intraocular pressure (IOP) elevation after intracameral injection into mouse eyes of SO, and removing the SO allows the IOP level to quickly return to normal. This simple, inducible and reversible mouse model showed dynamic changes of visual function that correlate with progressive RGC loss and axon degeneration. We also used a single AAV vector for the first time to co-express miRNA-based shRNA and a neuroprotective transgene and further validated this model as an effective in vivo means to test neuroprotective therapies by targeting neuronal endoplasmic reticulum stress.

neuroscience↗

bioRxiv2018

ALV-J and REV synergistically activate a new oncogene of KIAA1199 via NF-κB and EGFR signaling regulated by miR-147

The tumorigenesis is the result of the accumulation of multiple oncogenes and tumor suppressor genes changes. Co-infection of avian leucosis virus subgroup J (ALV-J) and reticuloendotheliosis virus (REV), as two oncogenic retroviruses, showed synergistic pathogenic effects characterized by enhanced tumor initiation and progression. The molecular mechanism underlying synergistic effects of ALV-J and REV on the neoplasia remains unclear. Here, we found co-infection of ALV-J and REV enhanced the ability of virus infection, increased viral life cycle, maintained cell survival and enhanced tumor formation. We combined the high-throughput proteomic readout with a large-scale miRNA screening to identify which molecules are involved in the synergism. Our results revealed co-infection of ALV-J and REV activated a latent oncogene of KIAA1199 and inhibited the expression of tumor suppressor miR-147. Further, enhanced KIAA1199, down-regulated miR-147, activated NF-{kappa}B and EGFR were demonstrated in co-infected tissues and tumor. Mechanistically, we showed ALV-J and REV synergistically enhanced KIAA1199 by activation of NF-{kappa}B and EGFR signalling pathway, and the suppression of tumor suppressor miR-147 was contributed to maintain the NF-{kappa}B/KIAA1199/EGFR pathway crosstalk by targeting the 3UTR region sequences of NF-{kappa}B p50 and KIAA1199. Our results contributed to the understanding of the molecular mechanisms of viral synergistic tumorgenesis, which provided the evidence that suggested the synergistic actions of two retroviruses could result in activation of latent pro-oncogenes.\n\nAuthor summaryThe tumorigenesis is the result of the accumulation of multiple oncogenes and tumor suppressor genes changes. Co-infection with ALV-J and REV showed synergistic pathogenic effects characterized by enhanced tumor progression, however, the molecular mechanism on the neoplasia remains unclear. Our results revealed co-infection of ALV-J and REV promotes tumorigenesis by both induction of a latent oncogene of KIAA1199 and suppression of the expression of tumor suppressor miR-147. Mechanistic studies revealed that ALV-J and REV synergistically enhance KIAA1199 by activation of NF-{kappa}B and EGFR signalling pathway, and the suppression of tumor suppressor miR-147 was contributed to maintain the NF-{kappa}B/KIAA1199/EGFR pathway crosstalk by targeting the 3UTR region sequences of NF-{kappa}B p50 and KIAA1199. These results provided the evidence that suggested the synergistic actions of two retroviruses could result in activation of latent pro-oncogenes, indicating the potential preventive target and predictive factor for ALV-J and REV induced tumorigenesis.

molecular biology↗