Biology subjects

Wong, I. Y.

Publications and source records attributed to Wong, I. Y..

7 recordsLinked to original sources

bioRxiv2026

Label-Free All-Electrical Tracking of Individual and Collective Cell Migration on a Megapixel CMOS Capacitance Sensor

Label-free tracking of adherent cell migration could enable important insights into biological processes such as tissue repair, inflammatory response, or cancer progression. Nevertheless, visualizing unlabeled animal cells using optical microscopy remains challenging due to low contrast as well as frequent changes in cell shape and number. A promising alternative uses electrical capacitance measurements, which are sensitive to cell adhesion to electrode surfaces. However, prior examples often utilized electrodes with areas larger than single cells, resulting in averaged readouts over multiple cells. Here, we demonstrate label-free, live-cell tracking using a capacitance sensor array with more than 1 million pixels on a 10 micron pitch across an area larger than 1 square centimeter. We show that single cell morphology can be clearly segmented, and then used to reconstruct migration and proliferation dynamics using optical flow. We further track the spreading of multicellular spheroids, revealing fast-moving peripheral regions led by a collective leader cell "front." Finally, we demonstrate label-free imaging of millimeter-scale honeycomb-shaped tissues without the multi-image stitching often required for conventional microscopy. We utilize mutual capacitance measurements with electrically-programmable electrode spacing to reconstruct topographical features of these engineered tissues. Overall, CMOS capacitance imaging arrays enables label-free imaging spanning from single cells to large tissues, in a portable and scalable format for settings where optical microscopy may be difficult to access.

bioengineering↗

bioRxiv2026

Partial EMT Drives Persistent Collective Migration via Collision Guidance in Heterogeneous Populations

The epithelial-mesenchymal transition (EMT) alters cell-cell interactions to facilitate collective or individual migration during embryonic development, wound repair, or tumor invasion. Epithelial cells are typically cohesive and stationary while mesenchymal cells are individually dispersed and motile. Additional "partial" EMT states are thought to occur with distinct adhesive and migratory behaviors, but these functional phenotypes are poorly understood. Here, we show that cells treated with moderate TGF-{beta} concentration exhibit collective migration that is fast and directionally persistent despite heterogeneity in epithelial, partial, and mesenchymal states. We find cells coordinate their motility by reorienting in similar directions after transient contacts, a distinct "collision guidance" mechanism that differs from epithelial arrest or mesenchymal repulsion. Moreover, partial EMT cells sustain collision guidance when interacting with epithelial or mesenchymal cells, which otherwise have increased tendency to repel. We corroborate these experimental observations with a computational model using self-propelled interacting particles that align their motion or repel upon contact. Finally, we show that partial EMT enables tissue monolayer fronts to overwhelm and displace monolayers of other cell types after collision. Overall, these results reveal that partial EMT promotes coherent and emergent behaviors that bridge from cell to tissue length scales, with potential implications for shaping epithelial tissue formation, regeneration, or disorganization.

biophysics↗

bioRxiv2025

Expression of vimentin intermediate filaments in epithelial cells promotes cell migration and cell matrix interaction in 3D

During a variety of physiological and pathological processes, such as development, wound healing, and tumor progression, epithelial cells collectively invade into their surroundings. Vimentin intermediate filaments (VIFs) are often observed to play a role in the epithelial cells located at the margins of 2D cultures. However, their role in 3D collective cell behavior remains underexplored. Here, we investigate how induced vimentin expression affects 3D multicellular architecture and mechanics in luminal breast cancer cells (MCF-7) that ordinarily express keratin intermediate filaments only. We find that vimentin expression significantly alters 3D cell cluster morphology, inducing protrusions and increasing boundary fluctuations. Furthermore, cells in vimentin-expressing clusters show enhanced, more stochastic migration. In addition, these clusters exert stronger and localized traction forces on the surrounding matrix, indicating increased cell-matrix interactions. Transcriptomic analysis corroborates these biophysical findings, revealing upregulated gene expression for cell migration and matrix adhesion, and downregulated cell-cell adhesion genes. Our results demonstrate that VIFs are critical in modulating 3D multicellular collective morphology and dynamics, promoting invasive-like behavior by enhancing cell migration and cell-matrix interactions. These results provide fundamental insights into understanding tissue morphogenesis and disease progression.

biophysics↗

bioRxiv2025

Collective Transitions from Orbiting to Matrix Invasion in 3D Multicellular Spheroids

Coordinated cell rotation along a curved matrix interface can sculpt epithelial tissues into spherical morphologies. Subsequently, radially-oriented invasion of multicellular strands or branches can occur by local remodeling of the confining matrix. These symmetry-breaking transitions emerge from the dynamic reciprocity between cells and matrix, but remain poorly understood. Here, we show that epithelial cell spheroids collectively transition from circumferential orbiting to radial invasion via bi-directional interactions with the surrounding matrix curvature. Initially, spheroids exhibit an ellipsoidal shape but become rounded as orbiting occurs. However, cells gradually reorient from coordinated rotation towards outward strand invasion due to the accumulation of contractile tractions at discrete sites. Remarkably, the initial ellipsoid morphology predicts subsequent invasion of 2-4 strands roughly aligned with the major axis. We then perturb collective migration using osmotic pressure, showing that orbiting can be arrested and invasion can be reversed. We also investigate coordinated orbiting in "mosaic" spheroids, showing a small fraction of "leader" cells with weakened cell-cell adhesions can impede collective orbiting but still invade into the matrix. Finally, we establish a minimal self-propelled particle model to elucidate how collective orbiting is mediated by the crosstalk of cell-cell and cell-matrix adhesion along a curved boundary. Altogether, this work elucidates how tissue morphogenesis is governed by the interplay of collective behaviors and the local curvature of the cell-matrix, with relevance for embryonic development and tumor progression.

biophysics↗

bioRxiv2024

Generative modeling of biological shapes and images using a probabilistic α-shape sampler

Understanding morphological variation is an important task in many areas of computational biology. Recent studies have focused on developing computational tools for the task of sub-image selection which aims at identifying structural features that best describe the variation between classes of shapes. A major part in assessing the utility of these approaches is to demonstrate their performance on both simulated and real datasets. However, when creating a model for shape statistics, real data can be difficult to access and the sample sizes for these data are often small due to them being expensive to collect. Meanwhile, the current landscape of generative models for shapes has been mostly limited to approaches that use black-box inference--making it difficult to systematically assess the power and calibration of sub-image models. In this paper, we introduce the -shape sampler: a probabilistic framework for generating realistic 2D and 3D shapes based on probability distributions which can be learned from real data. We demonstrate our framework using proof-of-concept examples and in two real applications in biology where we generate (i) 2D images of healthy and septic neutrophils and (ii) 3D computed tomography (CT) scans of primate mandibular molars. The -shape sampler R package is open-source and can be downloaded at https://github.com/lcrawlab/ashapesampler. Author SummaryUsing shapes and images to understand genotypic and phenotypic variation has proven to be an effective strategy in many biological applications. Unfortunately, shape data can be expensive to collect and, as a result, sample sizes for analyses are often small. Despite methodological advancements in shape statistics and machine learning, benchmarking standards for evaluating new computational tools via data simulation is still underdeveloped. In this paper, we present a probability-based pipeline called the -shape sampler which has the flexibility to generate new and unobserved shapes based on an input set of data. We extensively evaluate the generative capabilities of our pipeline using 2D cellular images of neutrophils and 3D mandibular molars from two different suborders of primates.

bioinformatics↗

bioRxiv2021

Somatic Mutations in Collagens are Associated with a Distinct Tumor Environment and Overall Survival in Gastric Cancer

BackgroundGastric cancer is a heterogeneous disease with poorly understood genetic and microenvironmental factors. Mutations in collagen genes are associated with genetic diseases that compromise tissue integrity, but their role in tumor progression has not been extensively reported. Aberrant collagen expression has been long associated with malignant tumor growth, invasion, chemoresistance, and patient outcomes. We hypothesized that somatic mutations in collagens could functionally alter the tumor extracellular matrix. MethodsWe used publicly available datasets including The Tumor Cancer Genome Atlas (TCGA) to interrogate somatic mutations in collagens in stomach adenocarcinomas. To demonstrate that collagens were significantly mutated above background mutation rates, we used a moderated Kolmogorov-Smirnov test along with combination analysis with a bootstrap approach to define the background accounting for mutation rates. Association between mutations and clinicopathological features was evaluated by Fisher or chi-squared tests. Association with overall survival was assessed by Kaplan-Meier and the Cox-Proportional Hazards Model. Gene Set Enrichment Analysis was used to interrogate pathways. Immunohistochemistry and in situ hybridization tested expression of COL7A1 in stomach tumors. ResultsIn stomach adenocarcinomas, we identified individual collagen genes and sets of collagen genes harboring somatic mutations at a high frequency compared to background in both microsatellite stable, and microsatellite instable tumors in TCGA. Many of the missense mutations resemble the same types of loss of function mutations in collagenopathies that disrupt tissue formation and destabilize cells providing guidance to interpret the somatic mutations. We identified combinations of somatic mutations in collagens associated with overall survival, with a distinctive tumor microenvironment marked by lower matrisome expression and immune cell signatures. Truncation mutations were strongly associated with improved outcomes suggesting that loss of expression of secreted collagens impact tumor progression and treatment response. Germline collagenopathy variants guided interpretation of impactful somatic mutations on tumors. ConclusionsThese observations highlight that many collagens, expressed in non-physiologically relevant conditions in tumors, harbor impactful somatic mutations in tumors, suggesting new approaches for classification and therapy development in stomach cancer. In sum, these findings demonstrate how classification of tumors by collagen mutations identified strong links between specific genotypes and the tumor environment. Research HighlightsCollagen mutations are prevalent in stomach cancer Collagen somatic missense mutations resemble collagenopathy mutations Collagen mutations associate with overall survival in stomach cancer Tumors with collagen mutations have distinct molecular pathways and tumor microenvironments

cancer biology↗

bioRxiv2019

Mechanophenotyping of 3D Multicellular Clusters using Displacement Arrays of Rendered Tractions

Epithelial tissues mechanically deform the surrounding extracellular matrix during embryonic development, wound repair, and tumor invasion. Ex vivo measurements of such multicellular tractions within three-dimensional (3D) biomaterials could elucidate collective dissemination during disease progression, and enable preclinical testing of targeted anti-migration therapies. However, past 3D traction measurements have been low throughput due to the challenges of imaging and analyzing information-rich 3D material deformations. Here, we demonstrate a method to profile multicellular clusters in a 96-well plate format based on spatially heterogeneous contractile, protrusive, and circumferential tractions. As a case study, we profile multicellular clusters across varying states of the epithelial-mesenchymal transition, revealing a successive loss of protrusive and circumferential tractions, as well as the formation of localized contractile tractions with elongated cluster morphologies. These cluster phenotypes were biochemically perturbed using drugs, biasing towards traction signatures of different epithelial or mesenchymal states. This higher-throughput analysis is promising to systematically interrogate and perturb aberrant mechanobiology, which could be utilized with human patient samples to guide personalized therapies.

bioengineering↗