Biology subjects

Zhao, Z.

Publications and source records attributed to Zhao, Z..

At least 289 records · Page 16Linked to original sources

bioRxiv2023

Integrative pan-cancer analysis reveals a common architecture of dysregulated transcriptional networks characterized by loss of enhancer methylation

Aberrant DNA methylation contributes to gene expression deregulation in cancer. However, these alterations precise regulatory role and clinical implications are still not fully understood. In this study, we performed expression-methylation Quantitative Trait Loci (emQTL) analysis to identify deregulated cancer-driving transcriptional networks linked to CpG demethylation pan-cancer. By analyzing 33 cancer types from The Cancer Genome Atlas, we identified and confirmed significant correlations between CpG methylation and gene expression (emQTL) in cis and trans, both across and within cancer types. Bipartite network analysis of the emQTL revealed groups of CpGs and genes related to important biological processes involved in carcinogenesis; specifically, we identified three types of emQTL networks associated with alterations linked to the regulation of proliferation, metabolism, and hormone-signaling. These bipartite communities were characterized by loss of enhancer methylation in transcription factor binding regions (TFBRs) located in enhancers. The underlying CpGs were topologically linked to upregulated genes through chromatin loops. Loss of enhancer methylation and target genes were exemplified in pancreatic cancer. Penalized Cox regression analysis showed a significant prognostic impact of the pan-cancer emQTL. Taken together, our integrative pan-cancer analysis reveals a common architecture of aberrant DNA demethylation that illustrates a convergence of pathological regulatory mechanisms across cancer types.

cancer biology↗

bioRxiv2023

Mapping Cell-to-cell Interactions from Spatially Resolved Transcriptomics Data

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently, through the introduction of spatially resolved transcriptomics technologies (SRTs), especially those that achieve single cell resolution. However, significant challenges remain to analyze such highly complex data properly. Here, we introduce a Bayesian multi-instance learning framework, spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight spacias power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates, and most importantly the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of spacia for all three commercialized single cell resolution ST technologies: MERSCOPE/Vizgen, CosMx/Nanostring, and Xenium/10X. Spacia unveiled how endothelial cells, fibroblasts and B cells in the tumor microenvironment contribute to Epithelial-Mesenchymal Transition and lineage plasticity in prostate cancer cells. We deployed spacia in a set of pan-cancer datasets and showed that B cells also participate in PDL1/PD1 signaling in tumors. We demonstrated that a CD8+ T cell/PDL1 effectiveness signature derived from spacia analyses is associated with patient survival and response to immune checkpoint inhibitor treatments in 3,354 patients. We revealed differential spatial interaction patterns between {gamma}{delta} T cells and liver hepatocytes in healthy and cancerous contexts. Overall, spacia represents a notable step in advancing quantitative theories of cellular communications.

bioinformatics↗

bioRxiv2023

Nuclear Lipid Droplets Exit to the Cytoplasm: A Novel Mechanism of non-nuclear pore-dependent material exchange

In cellular biology, the extrusion of large molecular complexes from the nucleus has consistently represented a considerable challenge. In this investigation, we reveal a hitherto unexplored mechanism facilitating the efflux of nuclear lipid droplets (nLDs) from the nucleus directly into the cytoplasm, a process integral to comprehending cellular processes and nuclear dynamics. Through high-throughput sequencing, immunoprecipitation, and immunofluorescence experimentation, we demonstrated that the type I nucleoplasmic reticulum engages with nLDs, enabling the dynamic protein Rab8as transfer to the nLDs and fostering their translocation to the nuclear membrane. Phosphorylation of LMNA/C at the S392 site, adjacent to the nLD-nuclear membrane contact site, induces local depolymerization of lamins, creating an aperture that enables gradual nuclear exit of nLDs. Following this, nLDs, carrying DNA fragments, are released into the cytoplasm through budding and subsequently undergo autophagy-mediated degradation. Furthermore, we demonstrate that RhoA-PKC signaling enhances nLD movement and LMNA/C phosphorylation, while its inhibition impedes nuclear nLD efflux. Our groundbreaking investigation illuminates non-nuclear pore-dependent mechanisms of material exchange and offers fresh perspectives on nuclear metabolic pathways. In Brief O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/556761v1_ufig1.gif" ALT="Figure 1"> View larger version (107K): org.highwire.dtl.DTLVardef@38a213org.highwire.dtl.DTLVardef@1898caorg.highwire.dtl.DTLVardef@d7270forg.highwire.dtl.DTLVardef@14582a2_HPS_FORMAT_FIGEXP M_FIG C_FIG In this study, Jin et al. elucidate a novel mechanism for the expulsion of nuclear lipid droplets (nLDs) from the nucleus. They demonstrate that the activation of RhoA within the nucleus recruits Rab8a to the surface of nLDs. Concurrently, PKC phosphorylation triggers the phosphorylation of LMNA/C at the S392 site, leading to a localized depolymerization of lamins. This creates an aperture that allows for the gradual exit of nLDs from the nucleus. The efflux process of nLDs involves three sequential steps: rupture of the nuclear fibril layer, fusion of nLDs with the inner nuclear membrane (INM), and subsequent fusion with the outer nuclear membrane (ONM). This enables nLDs to enter the cytoplasm, shedding light on a previously unknown process of large molecular entity expulsion from the nucleus.

molecular biology↗

bioRxiv2023

Pathogenic mitochondrial DNA mutations inhibit melanoma metastasis

Mitochondrial DNA (mtDNA) mutations are frequently observed in cancer, but their contribution to tumor progression is controversial. To evaluate the impact of mtDNA variants on tumor growth and metastasis, we created human melanoma cytoplasmic hybrid (cybrid) cell lines transplanted with wildtype mtDNA or pathogenic mtDNA encoding variants that partially or completely inhibit oxidative phosphorylation. Homoplasmic pathogenic mtDNA cybrids reliably established tumors despite dysfunctional oxidative phosphorylation. However, pathogenic mtDNA variants disrupted spontaneous metastasis of subcutaneous tumors and decreased the abundance of circulating melanoma cells in the blood. Pathogenic mtDNA did not induce anoikis or inhibit organ colonization of melanoma cells following intravenous injections. Instead, migration and invasion were reduced, indicating that limited circulation entry functions as a metastatic bottleneck amidst mtDNA dysfunction. Furthermore, analysis of selective pressure exerted on the mitochondrial genomes of heteroplasmic cybrid lines revealed a suppression of pathogenic mtDNA allelic frequency during melanoma growth. Collectively, these findings demonstrate that functional mtDNA is favored during melanoma growth and enables metastatic entry into the blood.

cancer biology↗

bioRxiv2023

WGCNA and Machine Learning for Screening Potential Biomarkers in traumatic brain injury

BackgroundTraumatic brain injury (TBI) is more common than ever and is becoming a global public health issue. However, there are no sensitive diagnostic or prognostic biomarkers to identify TBI, which leads to long-term consequences. In this study, we aim to identify genes that contribute to brain injury and to identify potential mechanisms for its progression in the early stages. MethodFrom the Gene Expression Omnibus (GEO) database, we downloaded GSE2871s gene expression profiles. Weighted gene coexpression network analyses (WGCNA) were conducted on differentially expressed genes (DEGs), and the DEGs were analyzed by Gene Set Enrichment Analysis(GSEA). An enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed for understanding the biological functions of genes. The potential biomarkers were identified using 3 kinds of machine learning algorithms. Nomogram was constructed using the "rms" package. And the receiver operating characteristic curve (ROC) was plotted to detect and validate our prediction model sensitivity and specifificity. ResultsBetween samples with and without brain injury, 107 DEGs were identified, including 47 upregulated genes and 60 downregulated genes. On the basis of WGCNA and DEGs, 97 target genes were identified. In addition, biological function analysis indicated that target genes were primarily involved in the interaction of neuroactive ligands with receptors, taste transduction, cortisol synthesis and secretion, potassium ion transport. Based on machine learning algorithms, LOC103691092, Npw could be potentially useful biomarkers for TBI and showed good diagnostic values. Finally, a nomogram was constructed of the expression levels of these seven target genes to predict level of TBI, and the ROC showed that these genes can be used as hub genes after TBI. ConclusionLOC103691092, NPW, STK39, KCND3, APOC3, FOXE3, and CHRNB1 were identified as hub genes of TBI. These findings can provide a new direction for the diagnosis and treatment of TBI.

neuroscience↗

bioRxiv2023

Cooperative progression of colitis and leukemia modulated by clonal hematopoiesis via PTX3/IL-1β pro-inflammatory signaling

Clonal hematopoiesis (CH) is considered an important risk factor for all-cause mortality and the development of multiple chronic diseases including hematological neoplasms, cardiovascular diseases, and potentially a range of autoimmune or immune-deficiency diseases. Mutations in TET2 are one of the first identified, most important, and prevalent genetic drivers of CH. However, cooperative factors and mechanisms underlying TET2-deficiency related CH (TedCH) remain largely unknown. Recently, it has been suggested that certain diseases occurred before TedCH and promote TedCH trajectory on the contrary, indicating that diseases in non-hematopoietic organs may act as environmental non-genetic drivers of CH. To clarify the relationships between immune-dysfunctional diseases and CH, here we tested the impact of various challenges on TedCH. We found that expedited TedCH depended on establishment of an inflammatory environment. Primary or chimeric Tet2-mutant mice spontaneously developed co-symptoms reminiscent of human chronic colitis and myeloid leukemia, which was exacerbated by feeding with DSS, an experimental inducer of ulcerative colitis. Single cell RNA-seq (scRNA-seq) analysis reveals in depth the damage of colon in the Tet2-mutant mice in physiological conditions or fed with DSS, along with increase of dysbacteriosis indicated by gut microbiome analysis. Results from colon scRNA-seq from both mouse and human highlight the important roles of PTX3/IL-1{beta} pro-inflammatory signaling in promoting colitis or leukemia. Finally, TedCH trajectory and inflammation in colon and bone marrow were ameliorated by treatment of IL-1R1 inhibitor Anakinra. Our study suggests that PTX3/IL-1{beta} signaling and clonal hematopoiesis cooperate and play important roles in gut-bone marrow axis and related diseases including colitis and leukemia. HighlightsO_LICertain environmental factors, such as Dextran Sulfate Sodium (DSS), an experimental inducer of ulcerative colitis, promote TedCH C_LIO_LIColitis and leukemia are spontaneously and simultaneously developed in Tet2-defficient primary or chimeric mice, along with increased pathogenic gut microbiomes, indicating an aberrant gut-bone marrow axis in the mutant mice. C_LIO_LISingle cell RNA-seq analysis reveals enhanced PTX3, a soluble pattern recognition molecule and IL-1{beta} pro-inflammatory signaling in colitis and leukemia. C_LIO_LIThe In vivo function of the PTX3/IL-1{beta} pro-inflammatory signaling in TedCH is indicated in human colitis and validated in experimental settings. C_LI

immunology↗

bioRxiv2023

The ubiquitin ligase STUB1 suppresses tumorigenesis of renal cell carcinomas through regulating YTHDF1 stability

STIP1 homology and U-box protein 1 (STUB1), a key RING family E3 ubiquitin ligase, plays both oncogenic and tumor-suppressive roles in a variety of human cancers. However, the role and mechanism of STUB1 in clear cell renal cell carcinoma (ccRCC) remains poorly defined. Here, we identified YTHDF1 as a novel STUB1 interactor by affinity purification mass spectrometry (AP-MS). STUB1 polyubiquitylates YTHDF1 and promotes YTHDF1 degradation. STUB1 depletion stabilizes YTHDF1 in renal cancer cells. STUB1-knockdown renal cancer cells exhibit increased migration and invasion in YTHDF1 dependent manner. Further study demonstrates that STUB1 knockdown promoted the tumorigenicity of ccRCC in a xenograft model. Clinically, STUB1 expression is down-regulated in ccRCC tissues, and the low expression level of STUB1 was associated with higher tumor stage and poor overall survival in patients with ccRCC. These findings reveal that STUB1 acts as an E3 ubiquitin ligase and promotes degradation of YTHDF1, and STUB1 inhibits the tumorigenicity of ccRCC through ubiquitinating YTHDF1. Novelty & Impact StatementsSTUB1 plays both oncogenic and tumor-suppressive roles in a variety of human cancers. Here, the authors demonstrated that STUB1 acts as a tumor suppressor in ccRCC, and the low expression level of STUB1 was associated with higher tumor stage and poor overall survival in patients with ccRCC. In addition, STUB1-knockdown renal cancer cells exhibit increased migration and invasion in YTHDF1 dependent manner. Mechanistically, STUB1 polyubiquitylates YTHDF1 and promotes YTHDF1 degradation.

cancer biology↗

bioRxiv2023

HSPA8-mediated stability of the CLPP protein regulates mitochondrial autophagy in cisplatin-resistant ovarian cancer cells

BackgroundCurrently, platinum agents remain the mainstay of chemotherapy for ovarian cancer (OC). However, cisplatin (DDP) resistance is a major reason for chemotherapy failure. Thus, it is extremely important to elucidate the mechanism of resistance to DDP. MethodsWe establish 2 DDP-resistant ovarian cancer cell lines and find that caseinolytic protease P (CLPP) is significantly downregulated in the DDP-resistant cell lines when compared to wild-type ovarian cancer cell lines (SK-OV-3 and OVcar3). Next, we investigate the functions of CLPP in the DDP-resistant and wild-type ovarian cancer cells using various assays including cell counting kit-8 assays, western blotting, immunofluorescent staining, and reactive oxygen species (ROS) and apoptosis detection. ResultsOur experiments show that CLPP knockdown significantly increase the half maximal inhibitory concentration (IC50) and mitophagy of wild-type SK-OV-3 and OVcar3 cells, while CLPP overexpression reduces the IC50 values and mitophagy of DDP-resistant SK-OV-3 and OVcar3 cells. Next, we perform database predictions and experiments to show that heat shock protein family A member 8 (HSPA8) regulates CLPP protein stability. The dynamic effects of the HSPA8/CLPP axis in the ovarian cancer cells were also examined. HSPA8 increases mitophagy and the IC50 values of SK-OV-3 and OVcar3 cells, but inhibits their ROS production and apoptosis. In addition, CLPP partly reverses the effects induced by HSPA8 in the SK-OV-3 and OVcar3 cells. ConclusionsCLPP increases the DDP resistance of ovarian cancer by inhibiting mitophagy and promoting cellular stress. Meanwhile, HSPA8 promotes the degradation of CLPP protein by inducing its stability.

cancer biology↗

bioRxiv2023

SAW: An efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics

The basic analysis steps of spatial transcriptomics involve obtaining gene expression information from both space and cells. This process requires a set of tools to be completed, and existing tools face performance issues when dealing with large data sets. These issues include computationally intensive spatial localization, RNA genome alignment, and excessive memory usage in large chip scenarios. These problems affect the applicability and efficiency of the process. To address these issues, a high-performance and accurate spatial transcriptomics data analysis workflow called Stereo-Seq Analysis Workflow (SAW) has been developed for the Stereo-Seq technology developed by BGI. This workflow includes mRNA spatial position reconstruction, genome alignment, gene expression matrix generation and clustering, and generate results files in a universal format for subsequent personalized analysis. The excutation time for the entire analysis process is [~]148 minutes on 1G reads 1*1 cm chip test data, 1.8 times faster than unoptimized workflow.

bioinformatics↗

bioRxiv2023

Tip60-mediated Rheb acetylation links palmitic acid with mTORC1 activation and insulin resistance

Differences in dietary fatty acid saturation impact glucose homeostasis and insulin sensitivity in vertebrates. Excess dietary intake of saturated fatty acids (SFAs) induces glucose intolerance and metabolic disorders. In contrast, unsaturated fatty acids (UFAs) elicit beneficial effects on insulin sensitivity. However, it remains elusive how SFAs and UFAs signal differentially toward insulin signaling to influence glucose homeostasis. Here, using a croaker model, we report that dietary palmitic acid (PA), but not oleic acid or linoleic acid, leads to dysregulation of mTORC1 signaling which provokes systemic insulin resistance and glucose intolerance. Mechanistically, using croaker primary myocytes, mouse C2C12 myotubes and HEK293T cells, we show that PA-induced mTORC1 activation is dependent on mitochondrial fatty acid {beta} oxidation. Notably, PA profoundly elevates acetyl-CoA derived from mitochondrial fatty acid {beta} oxidation which intensifies Tip60-mediated Rheb acetylation. Subsequently, the induction of Rheb acetylation facilitates hyperactivation of mTORC1 which enhances serine phosphorylation of IRS1 and simultaneously inhibits transcription of IRS1 through impeding TFEB nuclear translocation, leading to impairment of insulin signaling. Furthermore, targeted abrogation of acetyl-CoA produced from fatty acid {beta} oxidation or Tip60-mediated Rheb acetylation by pharmacological inhibition and genetic knockdown rescues PA-induced insulin resistance. Collectively, this study reveals a conserved acetylation-dependent mechanistic insight for understanding the link between fatty acids and insulin resistance, which may provide a potential therapeutic avenue to intervene in the development of T2D.

cell biology↗

bioRxiv2023

Bacterial degradation of ctenophore Mnemiopsis leidyi organic matter

Blooms of gelatinous zooplankton, an important source of protein-rich biomass in coastal waters, often collapse rapidly, releasing large amounts of labile detrital organic matter (OM) into the surrounding water. Although these blooms have the potential to cause major perturbations in the marine ecosystem, their effects on the microbial community and hence on the biogeochemical cycles have yet to be elucidated. We conducted microcosm experiments simulating the scenario experienced by coastal bacterial communities after the decay of a ctenophore (Mnemiopsis leidyi) bloom in the northern Adriatic Sea. Within 24 h, a rapid response of bacterial communities to the M. leidyi OM was observed, characterized by elevated bacterial biomass production and respiration rates. Compared to our previous microcosm study of jellyfish (Aurelia aurita s.l.), M. leidyi OM degradation revealed that, despite the fundamental genetic and biochemical differences between the two species, a similar pattern in the bacterial community response was observed. Combined metagenomic and metaproteomic analysis indicated that the degradation activity was mainly performed by Pseudoalteromonas, producing a large amount of proteolytic exoenzymes and exhibiting high metabolic activity. Interestingly, the reconstructed metagenome-assembled genome (MAG) of Pseudoalteromonas phenolica was almost identical (average nucleotide identity >99%) to the MAG previously reconstructed in our A. aurita microcosm study. Taken together our data suggest that blooms of different gelatinous zooplankton are likely triggering a consistent response from natural bacterial communities, with specific bacterial lineages driving the remineralization of the gelatinous OM. ImportanceJellyfish blooms are increasingly becoming a recurring seasonal event in marine ecosystems, characterised by a rapid build-up of gelatinous biomass that collapses rapidly. Although these blooms have the potential to cause major perturbations, their impact on marine microbial communities is largely unknown. We conducted an incubation experiment simulating a bloom of the ctenophore Mnemiopsis leidyi in the Northern Adriatic, where we investigated the bacterial response to the gelatinous biomass. We found that the bacterial communities actively degraded the gelatinous organic matter, and overall showed a striking similarity to the dynamics previously observed after a simulated bloom of the jellyfish Aurelia aurita s.l. In both cases we found that a single bacterial species, Pseudoalteromonas phenolica, was responsible for most of the degradation activity. This suggests that blooms of different jellyfish are likely to trigger a consistent response from natural bacterial communities, with specific bacterial species driving the remineralisation of gelatinous biomass.

microbiology↗

bioRxiv2023

Mega-Enhancer Bodies Organize Neuronal Long Genes in the Cerebellum

Exceptionally long genes and cis-regulatory enhancers are selectively activated in mammalian brain neurons, and these loci are mutation hotspots in neurological disorders. However, the organization of these large genomic elements at the level of chromosome folding, beyond local enhancer-promoter interactions, remains poorly understood. Here, we report the discovery of a nuclear subcompartment in the mouse cerebellum formed by near-megabase long enhancers and their associated long genes encoding synaptic or signaling proteins. Genomic regions within this subcompartment reside in the outer-half of the nucleus, separated from other transcriptionally active structures. Using an in vivo CRISPR genetic mini-screen, we uncover a specific role for the transcription factor Etv1 in coupling the compartmentalization of neuronal long genes with their expression. Together, our study defines mechanisms that organize transcriptionally active genes across chromosomes in the mammalian brain.

neuroscience↗

bioRxiv2023

T4SEpp: a pipeline integrated with protein language models effectively predicting bacterial type IV secreted effectors

Many pathogenic bacteria use type IV secretion systems(T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causeing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs, and compared their performance. An integrated model T4SEpp was assembled by a module searching full-length, signal sequence and effector domain homologs of known T4SEs, a machine learning module based on the hand-crafted features extracted from the signal sequences, and the third module containing three best-performing protein language pre-trained models. T4SEpp outperformed the other state-of-the-art (SOTA) software tools, achieving [~]0.95 sensitivity at a high specificity of [~]0.99, based on the assessment of an independent testing dataset. Additionally, we performed a comprehensive search among 8,761 bacterial species, leading to the discovery of 227 species belonging to 3 phyla and 117 genera that possess T4SSs. Furthermore, leveraging the power of T4SEpp, we successfully identified a grand total of 12,622 plausible T4SEs. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs, and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

bioinformatics↗

bioRxiv2023

Bestrophin-4 relays Hes4 and interacts with Twist1 to suppress epithelial-to-mesenchymal transition in colorectal cancer cells

AbstractBestrophin isoform 4 (BEST4) is a newly identified subtype of the calcium-activated chloride channel family. Analysis of colonic epithelial cell diversity by single cell RNA-sequencing has revealed the existence of a cluster of BEST4+ mature colonocytes in humans. However, if the role of BEST4 is involved in regulating tumour progression remains largely unknown. In this study, we demonstrate that BEST4 overexpression attenuates cell proliferation, colony formation, and mobility in colorectal cancer (CRC) in vitro, and impedes the tumor growth and the liver metastasis in vivo. BEST4 is coexpressed with hairy/enhancer of split 4 (Hes4) in the nucleus of cells, and Hes4 signals BEST4 by interacting with the upstream region of the BEST4 promoter. BEST4 is epistatic to Hes4 and downregulates Twist1, thereby inhibiting epithelial-to-mesenchymal transition (EMT) in CRC. Conversely, knockout of BEST4 using CRISPR/Cas9 in CRC cells revitalises tumor growth and induces EMT. Furthermore, the low level of the BEST4 mRNA is correlated with advanced and the worse prognosis, suggesting its potential role in regulating CRC progression.

cancer biology↗

bioRxiv2023

Enabling AI in Synthetic Biology through Construction File Specification

The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases Experiment objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.

synthetic biology↗

bioRxiv2023

Vacuolar H+-ATPase Determines Daughter Cell Fates through Asymmetric Segregation of the Nucleosome Remodeling and Deacetylase Complex

Asymmetric cell divisions (ACDs) generate two daughter cells with identical genetic information but distinct cell fates through epigenetic mechanisms. However, the process of partitioning different epigenetic information into daughter cells remains unclear. Here, we demonstrate that the nucleosome remodeling and deacetylase (NuRD) complex is asymmetrically segregated into the surviving daughter cell rather than the apoptotic one during ACDs in Caenorhabditis elegans. The absence of NuRD triggers apoptosis via the EGL-1-CED-9-CED-4-CED-3 pathway, while an ectopic gain of NuRD enables apoptotic daughter cells to survive. We identify the vacuolar H+-adenosine triphosphatase (V-ATPase) complex as a crucial regulator of NuRDs asymmetric segregation. V-ATPase interacts with NuRD and is asymmetrically segregated into the surviving daughter cell. Inhibition of V-ATPase disrupts cytosolic pH asymmetry and NuRD asymmetry. We suggest that asymmetric segregation of V-ATPase may cause distinct acidification levels in the two daughter cells, enabling asymmetric epigenetic inheritance that specifies their respective life-versus-death fates.

cell biology↗

bioRxiv2023

Human iPSC 4R tauopathy model uncovers modifiers of tau propagation

Tauopathies are age-associated neurodegenerative diseases whose mechanistic underpinnings remain elusive, partially due to lack of appropriate human models. Current human induced pluripotent stem cell (hiPSC)-derived neurons express very low levels of 4-repeat (4R)-tau isoforms that are normally expressed in adult brain. Here, we engineered new iPSC lines to express 4R-tau and 4R-tau carrying the P301S MAPT mutation when differentiated into neurons. 4R-P301S neurons display progressive Tau inclusions upon seeding with Tau fibrils and recapitulate features of tauopathy phenotypes, including shared transcriptomic signatures, autophagic body accumulation, and impaired neuronal activity. A CRISPRi screen of genes associated with Tau pathobiology identified over 500 genetic modifiers of Tau-seeding-induced Tau propagation, including retromer VPS29 and the UFMylation cascade as top modifiers. In AD brains, the UFMylation cascade is altered in neurofibrillary-tangle-bearing neurons. Inhibiting the UFMylation cascade suppressed seeding-induced Tau propagation. This model provides a powerful platform to identify novel therapeutic strategies for 4R tauopathy.

neuroscience↗

bioRxiv2023

WBSCR16 Determines Metabolic Flexibility Via Regulating Mitochondrial 16S rRNA Maturation

Mitochondria play significant roles in energy homeostasis by dissipating excess calories. However, the key proteins in mitochondrial govern metabolically flexibility remain poorly understand. Herein, we generated adipose specific Wbscr16-/-mice and cells, both of which exhibited a preference for fat utilization and displayed dramatic mitochondrial changes. We demonstrated that WBSCR16 is essential for the specific cleavage of 16S rRNA-tRNALeu, leading to the production of maturated 16S rRNA, which in turn controls mitochondrial large ribosomal assembly. Importantly, WBSCR16 was identified as a 16S rRNA-binding protein that directly interacts with RNase P subunit MRPP3. Furthermore, evidence showed that WBSCR16 ablation promotes energy wasting via lipid cycling in BAT, leading to excess energy expenditure and resistance to obesity. Conversely, cells and mice with WBSCR16 overexpression preferred to glucose utilization. These findings suggest that WBSCR16 is the key mitochondrial switch protein between glucose and lipid metabolism, making it a promising target for the development of fat busting drug.

cell biology↗