Biology subjects

Zi, Z.

Publications and source records attributed to Zi, Z..

5 recordsLinked to original sources

bioRxiv2024

COCOA: A Framework for Fine-scale Mapping Cell-type-specific Chromatin Compartmentalization Using Epigenomic Information

Chromatin compartmentalization and epigenomic modification are crucial factors in cell differentiation and diseases development. However, mapping precise chromatin compartmental patterns across multiple cell types requires Hi-C or Micro-C data at high sequencing depth. Exploring the systematic relationship between epigenomic modifications and compartmental patterns remains a challenge. To address these issues, we present COCOA, a deep neural network framework that uses convolution and attention mechanisms to infer reliable fine-scale chromatin compartment patterns from six representative histone modification signals. COCOA achieves this by extracting 1-D track features through bi-directional feature reconstruction after resolution-specific binning epigenomic signals. These track features are then cross-fused with contact features using an attention mechanism. Subsequently, the contact features are transformed into chromatin compartment patterns through residual feature reduction. COCOA demonstrates accurate inference of chromatin compartmentalization at a fine-scale resolution and exhibits stable performance on test sets. In addition, we explored the impact of histone modifications on the chromatin compartmentalization through in silico epigenomic perturbation experiments. When using 1kb resolution high-depth experimental data, obscure compartments are observed, whereas COCOA can generate clear and detailed compartmental patterns. Finally, we demonstrated that COCOA enables cell-type-specific prediction of unrevealed chromatin compartment patterns in various biological processes. Thus, COCOA is an effective tool for gaining chromatin compartmentalization insights from epigenomics in a wide range of biological scenarios.

bioinformatics↗

bioRxiv2023

Liebig's law of the minimum in the TGF-β pathway

Cells use signaling pathways to sense and respond to their environments. The transforming growth factor-{beta} (TGF-{beta}) pathway produces context-specific responses. Here, we combined modeling and experimental analysis to study the dependence of the output of the TGF-{beta} pathway on the abundance of signaling molecules in the pathway. We showed that the TGF-{beta} pathway processes the variation of TGF-{beta} receptor abundance using Liebigs law of the minimum, meaning that the output-modifying factor is the signaling protein that is most limited, to determine signaling responses across cell types and in single cells. We found that the abundance of either the type I (TGFBR1) or type II (TGFBR2) TGF-{beta} receptor determined the responses of cancer cell lines, such that the receptor with relatively low abundance dictates the response. Furthermore, nuclear SMAD2 signaling correlated with the abundance of TGF-{beta} receptor in single cells depending on the relative expression levels of TGFBR1 and TGFBR2. A similar control principle could govern the heterogeneity of signaling responses in other signaling pathways. One-sentence summaryHeterogeneous TGF-{beta} signaling responses are dictated by the low abundance TGF-{beta} receptor in different cell types and in single cells, resembling Liebigs law of the minimum.

systems biology↗

bioRxiv2022

Cell division history encodes directional information of fate transitions

Single-cell RNA-sequencing (scRNA-seq) enables systematic mapping of cellular differentiation trajectories. However, inferring the cell-fate transitions under diseases or perturbations is still challenging due to the high cellular plasticity. Here, we demonstrate that monotonically expressed genes (MEGs) along cell divisions record the directions of state transitions regardless of the cellular processes. We developed a computational framework (PhyloVelo) to identify MEGs and reconstruct a novel transcriptomic velocity field by leveraging both scRNA-seq and phylogenetic information. PhyloVelo accurately recovered linear, bifurcated and convergent differentiations in simulations and C. elegans. It outperformed current approaches for delineating cellular trajectories in embryo development and tumor evolution through analysis of five CRISPR/Cas9-based lineage tracing datasets. Together, our study unveils an internal cellular clock and provides a powerful method for cellfate analysis in diverse biological contexts.

genomics↗

bioRxiv2021

Pro70 Hydroxylation of Actin Impairs Cell Motility Through Binding with VHL and Blocking His73 Methylation

Actin filaments generate intrinsic forces that are essential for cell motility. This process is tightly regulated by various posttranslational modifications (PTMs), including acetylation, arginylation, and oxidation. However, the role of actin hydroxylation in regulating its dynamics remains poorly understood. Here, we demonstrate that the inhibition of Prolyl Hydroxylase Domain-containing proteins (PHDs) activity significantly promotes actin polymerization and enhances cell motility. Using hydroxylation proteomics, we identified actin as a substrate for PHDs, with hydroxylation occurring at multiple proline residues, especially at proline 70 (Pro70). This modification recruits the von Hippel-Lindau (VHL) tumor suppressor protein, which then leads to the disruption of the interaction between actin and the histidine methyltransferase SET Domain Containing 3 (SETD3). Consequently, SETD3-mediated methylation of histidine 73 (His73) on actin is suppressed, impairing actin polymerization and compromising cell motility. Notably, genetic loss of VHL or pharmacological inhibition of PHDs restores His73 methylation, enhances actin filament formation, and promotes cell motility. Together, our findings uncover a novel regulatory crosstalk between hydroxylation and methylation on actin, establishing a critical mechanism by which PTMs fine-tune actin dynamics to govern cell motility. HighlightsO_LIMK-8617 augments cell motility and actin polymerization in VHL dependent manner; C_LIO_LIHydroxylation proteomics reveals that actin is hydroxylated by PHDs; C_LIO_LIHydroxylation at Pro70 recruits VHL, disrupting actins interaction with SETD3 and reducing His73 methylation; C_LIO_LIGenetic loss of VHL in clear cell renal cell carcinoma (ccRCC) potentially promotes cell motility by increasing His73 methylation on actin. C_LI

biochemistry↗

bioRxiv2021

Quantitative Phosphoproteomic Analyses Identify STK11IP as a Lysosome-Specific Substrate of mTORC1 that Regulates Lysosomal Acidification

The evolutionarily conserved serine/threonine kinase mTORC1 is a central regulator of cell growth and proliferation. mTORC1 is activated on the lysosome surface. However, once mTORC1 is activated, it is unclear whether mTORC1 phosphorylates local lysosomal proteins to regulate specific aspects of lysosomal biology. Through cross-reference analyses of lysosome proteomic with mTORC1-regulated phosphoproteomic, we identified STK11IP as a novel lysosome-specific substrate of mTORC1. mTORC1 directly phosphorylates STK11IP at S404. Knockout of STK11IP led to a robust increase of autophagosome-lysosome fusion and autophagy flux. Dephosphorylation of STK11IP at S404 represses the role of STK11IP as an autophagy inhibitor. Mechanistically, STK11IP binds to V-ATPase, and regulates the activity of V-ATPase. Knockout of STK11IP protects mice from fasting and Methionine and Choline-Deficient Diet (MCD) diet induced fatty liver. Thus, our study demonstrates that STK11IP phosphorylation represents a novel mechanism for mTORC1 to regulate lysosomal acidification, and points to STK11IP as a promising therapeutic target for the amelioration of diseases with aberrant autophagy signaling.

cell biology↗