Biology subjects

Yang, W.-T.

Publications and source records attributed to Yang, W.-T..

4 recordsLinked to original sources

bioRxiv2021

Actin filaments act as a size-dependent diffusion barrier around centrosomes

The centrosome, a non-membranous organelle, constrains various soluble molecules locally to execute its functions. As the centrosome is surrounded by various dense components, we hypothesized that the centrosome may be bordered by a putative diffusion barrier. After quantitatively measuring the trapping kinetics of soluble proteins of varying size at centrosomes by a chemically inducible diffusion trapping assay, we found that centrosomes were highly accessible to soluble molecules with a Stokes radius of [≤] 5.1 nm, whereas larger molecules rarely reach centrosomes, indicating the existence of a size-dependent diffusion barrier at centrosomes. The permeability of barriers was tightly regulated by branched actin filaments outside of centrosomes. Such barrier gated the microtubule nucleation. We propose that actin filaments spatiotemporally constrain the distribution of molecules at centrosomes in a size-dependent manner. Significance StatementCentrosome maintains its microenvironment without membrane. Whether the dense protein complexes outside centrosomes including pericentriolar matrix, microtubules, and branched actin filaments provide physical obstruction is unclear yet. We here established a series of new tools for quantitative evaluation of the diffusion rates of varisized soluble proteins in different sub-compartments of centrosomes. Our results demonstrated that branched actin filaments, but not pericentriolar matrix or microtubules, around centrosome have acted as a size-dependent diffusion barrier and physically constrain centrosome microtubule nucleation.

cell biology↗

bioRxiv2021

Precise control of microtubule disassembly in living cells

Microtubules (MTs) are components of the evolutionarily conserved cytoskeleton, which tightly regulates various cellular activities. Our understanding of MTs is largely based on MT-targeting agents, which, however, are insufficient to dissect the dynamic mechanisms of specific MT populations due to their slow effects on the entire pool of MTs in cells. To address this limitation, we have used chemogenetics and optogenetics to disassemble specific MT subtypes by rapid recruitment of engineered MT-cleaving enzymes. Acute MT disassembly swiftly halted vesicular trafficking and lysosome dynamics. We also used this approach to disassemble MTs specifically modified by tyrosination and several MT-based structures including primary cilia, mitotic spindles, and intercellular bridges. These effects were rapidly reversed by inhibiting the activity or MT association of the cleaving enzymes. The disassembly of targeted MTs with spatial and temporal accuracy enables to uncover new insights of how MTs precisely regulate cellular architectures and functions.

cell biology↗

bioRxiv2020

accuEnhancer: Accurate enhancer prediction by integration of multiple cell type data with deep learning

Enhancers are one class of the regulatory elements that have been shown to act as key components to assist promoters in modulating the gene expression in living cells. At present, the number of enhancers as well as their activities in different cell types are still largely unclear. Previous studies have shown that enhancer activities are associated with various functional data, such as histone modifications, sequence motifs, and chromatin accessibilities. In this study, we utilized DNase data to build a deep learning model for predicting the H3K27ac peaks as the active enhancers in a target cell type. We propose joint training of multiple cell types to boost the model performance in predicting the enhancer activities of an unstudied cell type. The results demonstrated that by incorporating more datasets across different cell types, the complex regulatory patterns could be captured by deep learning models and the prediction accuracy can be largely improved. The analyses conducted in this study demonstrated that the cell type-specific enhancer activity can be predicted by joint learning of multiple cell type data using only DNase data and the primitive sequences as the input features. This reveals the importance of cross-cell type learning, and the constructed model can be applied to investigate potential active enhancers of a novel cell type which does not have the H3K27ac modification data yet. AvailabilityThe accuEnhancer package can be freely accessed at: https://github.com/callsobing/accuEnhancer

bioinformatics↗

bioRxiv2019

NF-YA Transcriptionally Activates the Expression of SOX2 in Cervical Cancer Stem Cells

Roles for SOX2 have been extensively studied in several types of cancer, including colorectal cancer, glioblastoma and breast cancer, with particular emphasis placed on the roles of SOX2 in cancer stem cell. Our previous study identified SOX2 as a marker in cervical cancer stem cells driven by a full promoter element of SOX2 EGFP reporter. Here, dual-luciferase reporter and mutagenesis analyses were employed, identifying key cis-elements in the SOX2 promoter, including binding sites for SOX2, OCT4 and NF-YA factors in SOX2 promoter. Mutagenesis analysis provided additional evidence to show that one high affinity-binding domain CCAAT box was precisely recognized and bound by the transcription factor NF-YA. Furthermore, overexpression of NF-YA in primitive cervical cancer cells SiHa and C33A significantly activated the transcription and the protein expression of SOX2. Collectively, our data identified NF-YA box CCAAT as a key cis-element in the SOX2 promoter, suggesting that NF-YA is a potent cellular regulator in the maintenance of SOX2-positive cervical cancer stem cell by specific transcriptional activation of SOX2.

cancer biology↗