Biology subjects

Chou, T.-C.

Publications and source records attributed to Chou, T.-C..

4 recordsLinked to original sources

bioRxiv2026

Behavior-coupled single-cell transcriptomics reveals trafficking protein-dependent regulation of tumor cell migration

Aggressive cellular migration underlies cancer invasion and metastatic dissemination, yet the molecular programs defining highly migratory tumor cell states remain poorly characterized. In head and neck squamous cell carcinoma (HNSCC), metastatic progression is associated with poor clinical outcome, motivating method developments that link migratory behavior to underlying mechanisms. Here, we present behavior-coupled single-cell sequencing (BC-seq), a live-cell imaging-guided transcriptomic platform that enables real-time identification, isolation, and profiling of individual cells based on migratory behavior. Applying BC-seq to 10 HPV-negative oral squamous cell carcinoma (OSCC), the most common HNSCC subtype, we distinguished fast-migrating cells (FMCs) from slow-migrating cells (SMCs) and identified transcriptional programs associated with aggressive migration. Mechanistically, BC-seq uncovered cholesterol-regulated signaling pathways and associated trafficking proteins involving SREBP2, STARD4, Cavin1/3, and VEGFR2 that promotes actin cytoskeletal remodeling and cellular motility. Disruption of STARD4-mediated cholesterol trafficking or Cavin1/3-dependent VEGFR2 nuclear translocation significantly impaired cell migration, linking cholesterol metabolism to migratory machinery. We next examined whether molecular programs associated with aggressive migration are reflected in clinical outcomes. A 15-gene expression signature derived from FMCs predicted distant metastasis with 83.6% accuracy in an independent OSCC cohort, outperforming conventional clinicopathological risk stratification. Together, our study establishes BC-seq as an approach for integrating dynamic cellular behavior with single-cell transcriptomics to uncover mechanisms of aggressive migration and clinically relevant molecular signatures.

cancer biology↗

bioRxiv2023

Fast and Accurate Cell Tracking: a real-time cell segmentation and tracking algorithm to instantly export quantifiable cellular characteristics from large scale image data

Quantitative characterizations of cellular dynamics and features of individual cells from a large heterogenous population is essential to identify rare, disease-driving cells, which often exhibit aberrant cellular behaviors like abnormal division, aggressive migration or irregular phylogenetic cell lineages. A recent development in the combination of high-throughput screening microscopy with single cell profiling provides an unprecedented opportunity to decipher the underlying mechanisms of disease-driving phenotypes observed under a microscope. However, accurately and instantly processing large amounts of image data like longitudinal time lapse movies remains a technical challenge when an immediate analysis output (in minutes) of quantitative characterizations is required after data acquisition. Here we present a Fast and Accurate real-time Cell Tracking (FACT) algorithm, which combines GPU-based, ground truth-assisted trainable Weka segmentation and real-time Gaussian mixture model-based cell linking. FACT also implements an automatic cell track correction function to improve the tracking accuracy. With FACT, we can segment [~]20,000 cells in 2 seconds ([~]4.5-27.5 times faster than state-of-the-art), and can export quantifiable features from the cell tracking results minutes after data acquisition (independent of the number of acquired image frames) with average 90-95% tracking precision. Such performance is not feasible with state-of-the-art cell tracking algorithms. We applied FACT to real-time identify directionally migrating glioblastoma cells with 96% precision and to identify rare, irregular cell lineages in a population of [~]10,000 cells from a 24hr-time lapse movie with an average 91% F1 score, results from both were exported instantly, mere minutes after image acquisition.

bioengineering↗

bioRxiv2021

Functional single cell selection and annotated profiling of dynamically changing cancer cells

A method connecting single cell genomic or transcriptomic profiles to functional cellular characteristics, in particular time-varying phenotypic changes, would be transformative for single cell and cancer biology. Here, we present fSCS: functional single cell selection. This technology combines a custom-built ultrawide field-of-view optical screening microscope, fast automated image analysis and a new photolabeling method, phototagging, using a newly synthesized visible-light-photoactivatable dye. Using fSCS, we screen, selectively photolabel and isolate cells of interest from large heterogeneous populations based on functional dynamics like fast migration, morphological variation, small molecule uptake or cell division. We combined fSCS with single cell RNA sequencing for functionally annotated transcriptomic profiling of fast migrating and spindle-shaped MCF10A cells with or without TGF{beta} induction. We identified critical genes and pathways driving aggressive migration as well as mesenchymal-like morphology that could not be detected with state-of-the-art single cell transcriptomic analysis. fSCS provides a crucial upstream selection paradigm for single cell sequencing independent of biomarkers, allows enrichment of rare cells and can facilitate the identification and understanding of molecular mechanisms underlying functional phenotypes.

bioengineering↗

bioRxiv2019

S. cerevisiae Srs2 helicase ensures normal recombination intermediate metabolism during meiosis and prevents accumulation of Rad51 aggregates

We investigated the meiotic role of Srs2, a multi-functional DNA helicase/translocase that destabilizes Rad51-DNA filaments, and is thought to regulate strand invasion and prevent hyper-recombination during the mitotic cell cycle. We find that Srs2 activity is required for normal meiotic progression and spore viability. A significant fraction of srs2 mutant cells progress through both meiotic divisions without separating the bulk of their chromatin, although sister centromeres often separate. Undivided nuclei contain aggregates of Rad51 colocalized with the ssDNA-binding protein RPA, suggesting the presence of persistent single-strand DNA. Rad51 aggregate formation requires Spo11-induced DSBs, Rad51 strand-invasion activity, and progression past the pachytene stage of meiosis, but not the DSB end-resection or the bias towards inter-homologue strand invasion characteristic of normal meiosis. srs2 mutants also display altered meiotic recombination intermediate metabolism, revealed by defects in the formation of stable joint molecules. We suggest that Srs2, by limiting Rad51 accumulation on DNA, prevents the formation of aberrant recombination intermediates that otherwise would persist and interfere with normal chromosome segregation and nuclear division.

genetics↗