Biology subjects

Gihana, G. M.

Publications and source records attributed to Gihana, G. M..

4 recordsLinked to original sources

bioRxiv2026

Modulation of Oncogenic KRAS Signaling by Branched Actin-driven Cell Membrane Protrusions

For over three decades, we have known that oncogenic RAS alters the actin cytoskeleton organization and cell surface morphology1,2. RAS activates the GTPase RAC1, which triggers the growth of branched actin networks to promote cell membrane protrusions3,4. In melanoma, the hyperactive RAC1 mutant, Rac1P29S, was recently shown to drive extended lamellipodia, which then empower cell proliferation through sequestration and localized inhibition of the merlin tumor suppressor5. This discovery illustrates cell morphological programs not only as outputs but also as regulators of human oncogenic signals. Hence, we wondered whether the pronounced branched actin-driven membrane protrusions (BAMPs) downstream of oncogenic RAS are not mere outputs of RAS signaling but rather an active component in mediating the oncogenic penetrance of RAS mutants. We used volumetric light sheet microscopy and biochemical approaches to investigate the role of BAMPs in regulating the molecular signaling of oncogenic KRAS in pancreatic and lung cancer models. We found that elevated BAMP formation regulated the interaction of oncogenic KRAS with downstream effectors, specifically with the RAC1 GEF TIAM1. This implies that BAMPs amplify their own upstream regulators in a positive feedback. This meritorious cycle upregulates cyclin D1 expression by inactivating the merlin tumor suppressor, independently of the mitogen activated protein kinase pathway (MAPK). In the absence of BAMPs, cells carrying oncogenic KRAS mutations are unable to attain their full penetrance in proliferation. Overall, this work unveils the long-overlooked role of branched actin-driven cell morphology in the functionalization of KRAS mutants as potent oncogenes.

cancer biology↗

bioRxiv2024

A general algorithm for consensus 3D cell segmentation from 2D segmented stacks

Cell segmentation is the foundation of a wide range of microscopy-based biological studies. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation, and computation. However, 3D cell segmentation, requiring dense annotation of 2D slices still poses significant challenges. Manual labeling of 3D cells to train broadly applicable segmentation models is prohibitive. Even in high- contrast images annotation is ambiguous and time-consuming. Here we develop a theory and toolbox, u- Segment3D, for 2D-to-3D segmentation, compatible with any 2D method generating pixel-based instance cell masks. u-Segment3D translates and enhances 2D instance segmentations to a 3D consensus instance segmentation without training data, as demonstrated on 11 real-life datasets, >70,000 cells, spanning single cells, cell aggregates, and tissue. Moreover, u-Segment3D is competitive with native 3D segmentation, even exceeding when cells are crowded and have complex morphologies.

bioinformatics↗

bioRxiv2023

Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D

Many signalling circuits are governed by the spatiotemporal organization of membrane-associated molecules. Growing evidence suggests that the mesoscale cell surface geometry is central in modulating this interplay. However, defining the causal hierarchy between geometric and molecular factors that control signals remains challenging. Nonlinearity and redundancy among the components prevent direct experimental perturbation, with shape being the most difficult to independently control. Towards the goal of inferring causality from observational data, we developed u-Unwrap3D as a resource to map arbitrarily complex 3D cell surfaces to diverse representations, each designed to interrogate a different aspect of the dynamic interaction between cell surface geometry and molecular cues. Using u-Unwrap3D, we discover a retrograde protrusion flow on natural killer cells associated with immunological synapse formation with cancer; establish a causal association of K14+ cells with breast tumor organoid invasion; measure the speed of ruffles; and quantify bleb-mediated assembly of septin polymers at the membrane.

bioinformatics↗

bioRxiv2022

Increasing the Field-of-View in Oblique Plane Microscopy via optical tiling

Fast volumetric imaging of large fluorescent samples with high-resolution is required for many biological applications. Oblique plane microscopy (OPM) provides high spatiotemporal resolution, but the field of view is typically limited by its optical train and the pixel number of the camera. Mechanically scanning the sample or decreasing the overall magnification of the imaging system can partially address this challenge, albeit by reducing the volumetric imaging speed or spatial sampling, respectively. In this Letter, we introduce a novel dual-axis scan unit for OPM that enables rapid and high-resolution volumetric imaging throughout a volume of 800 x 500 x 200 microns. This enables imaging of model organisms, such as zebrafish embryos, with subcellular resolution. Furthermore, we combined this microscope with a real-time and multi-perspective projection imaging technique to increase the volumetric interrogation rate to more than 10 Hz.

bioengineering↗