Biology subjects

Ni, Q.

Publications and source records attributed to Ni, Q..

22 records · Page 2Linked to original sources

bioRxiv2021

Different translation dynamics of β- and γ-actin regulates cell migration

{beta}- and {gamma}-cytoplasmic actins are ubiquitously expressed in every cell type and are nearly identical at the amino acid level but play vastly different roles in vivo. Their essential roles in embryogenesis and cell migration critically depend on the nucleotide sequences of their genes, rather than their amino acid sequence. However it is unclear which gene elements underlie this effect. Here we address the specific role of the coding sequence in {beta}- and {gamma}-cytoplasmic actins intracellular functions, using stable cell lines with exogenously expressed actin isoforms and their "codon-switched" variants. When targeted to the cell periphery using the {beta}-actin 3'UTR, {beta}-actin and {gamma}-actin have differential effects on cell migration. These effects directly depend on the coding sequence. Single molecule measurements of actin isoform translation, combined with fluorescence recovery after photobleaching, demonstrate a pronounced difference in {beta}- and {gamma}-actins translation elongation rates, leading to changes in their dynamics at focal adhesions, impairments in actin bundle formation, and reduced cell anchoring to the substrate during migration. Our results demonstrate that coding sequence-mediated differences in actin translation play a key role in cell migration.

cell biology↗

bioRxiv2020

TIPS: Trajectory Inference of Pathway Significance through Pseudotime Comparison for Functional Assessment of single-cell RNAseq Data

Recent advances in bioinformatics analyses have led to the development of novel tools enabling the capture and trajectory mapping of single-cell RNA sequencing (scRNAseq) data. However, there is a lack of methods to assess the contributions of biological pathways and transcription factors to an overall developmental trajectory mapped from scRNAseq data. In this manuscript, we present a simplified approach for trajectory inference of pathway significance (TIPS) that leverages existing knowledgebases of functional pathways and transcription factor targets to enable further mechanistic insights into a biological process. TIPS returns both the key pathways whose changes are associated with the process of interest, as well as the individual genes that best reflect these changes. TIPS also provides insight into the relative timing of pathway changes, as well as a suite of visualizations to enable simplified data interpretation of scRNAseq libraries generated using a wide range of techniques. The TIPS package can be run through either a web server, or downloaded as a user-friendly GUI run in R, and may serve as a useful tool to help biologists perform deeper functional analyses and visualization of their single-cell and/or large cohort RNAseq data.

bioinformatics↗

bioRxiv2020

scSTATseq: Diminishing Technical Dropout Enables Core Transcriptome Recovery and Comprehensive Single-cell Trajectory Mapping

The advent of single-cell RNA sequencing has provided illuminating information on complex systems. However, large numbers of genes tend to be scarcely detected in common scRNAseq approaches due to technical dropout. Although bioinformatics approaches have been developed to approximate true expression profiles, assess the dropout events on single-cell transcriptomes is still consequently challenging. In this report, we present a new plate-based method for scRNAseq that relies on Tn5 transposase to tagment cDNA following second strand synthesis. By utilizing pre-amplification tagmentation step, scSTATseq libraries are insulated against technical dropout, allowing for detailed analysis of gene-gene co-expression relationships and mapping of pathway trajectories. The entire scSTATseq library construction workflow can be completed in 7 hours, and recover transcriptome information on up to 8,000 protein-coding genes. Investigation of osteoclast differentiation using this workflow allowed us to identify novel markers of interest such as Rab15. Overall, scSTATseq is an efficient and economical method for scRNAseq that compares favorably with existing workflows.

genomics↗

bioRxiv2020

Tensile Force Induced Cytoskeletal Reorganization: Mechanics Before Chemistry

Understanding cellular remodeling in response to mechanical stimuli is a critical step in elucidating mechano-activation of biochemical signaling pathways. Experimental evidence indicates that external stress-induced subcellular adaptation is accomplished through dynamic cytoskeletal reorganization. To study the interactions between subcellular structures involved in transducing mechanical signals, we combined experimental and computational simulations to evaluate real-time mechanical adaptation of the actin cytoskeletal network. Actin cytoskeleton was imaged at the same time as an external tensile force was applied to live vascular smooth muscle cells using a fibronectin-functionalized atomic force microscope probe. In addition, we performed computational simulations of active cytoskeletal networks under a tensile external force. The experimental data and simulation results suggest that mechanical structural adaptation occurs before chemical adaptation during filament bundle formation: actin filaments first align in the direction of the external force, initializing anisotropic filament orientations, then the chemical evolution of the network follows the anisotropic structures to further develop the bundle-like geometry. This finding presents an alternative, novel explanation for the stress fiber formation and provides new insight into the mechanism of mechanotransduction. Author SummaryRemodeling the cytoskeletal network in response to external force is key to mechanosensing and locomotion. Despite much focus on cytoskeletal remodeling in recent years, a comprehensive understanding of actin remodeling in real-time in cells under mechanical stimuli is still lacking. We integrated stress-induced 3D actin imaging and 3D computational simulations of actin cytoskeleton to study how the actin cytoskeleton form bundles and how these bundles evolve over time upon external tensile stress. We found a rapid actin alignment and a slower bundle evolution leading to denser bundles. Based on these results, we propose a "mechanics before chemistry" model of actin cytoskeleton remodeling under external force.

cell biology↗